УПРАВЛЕНИЕ ПРОГРАММАМИ-КОМПОНЕНТАМИ В СЛУЖЕБНОМ ПРИЛОЖЕНИИ

... 1. Один или более компьютерных носителей информации, имеющих машиноисполняемые инструкции, реализованные на них, которые, когда исполняются, выполняют способ управления одной или более программами-компонентами в служебном приложении согласно модели обслуживания, причем способ содержит этапы, на которых: ! определяют (305) уровень нагрузки на служебное приложение, при этом служебное приложение содержит одну или более программ-компонентов, которые являются выполняемыми на отдельных вычислительных устройствах в центре обработки данных; ! извлекают (310) из модели обслуживания настройки конфигурации, которые могут применяться к одной или более программ-компонентов; ! инициируют (315) процесс реализации для управления служебным приложением в соответствии с уровнем нагрузки, процесс реализации содержит: ! (1) развертывание (320) одной или более программ-компонентов в центре обработки данных; и ! (2) автоматическое распространение (330) формализованных значений, полученных из настроек конфигурации ...

СПОСОБ И УСТРОЙСТВО ДЛЯ ИСПОЛНЕНИЯ ПРИЛОЖЕНИЯ В СИСТЕМЕ БЕСПРОВОДНОЙ СВЯЗИ

СТРУКТУРА КОМПЬЮТЕРНОГО КЛАСТЕРА ДЛЯ ВЫПОЛНЕНИЯ ВЫЧИСЛИТЕЛЬНЫХ ЗАДАЧ И СПОСОБ ФУНКЦИОНИРОВАНИЯ УКАЗАННОГО КЛАСТЕРА

... 1. Структура компьютерного кластера для обработки вычислительной задачи, содержащая:множество вычислительных узлов (CN), каждый из которых взаимодействует с инфраструктурой связи (IN), при этом по меньшей мере два из указанных вычислительных узлов размещены для совместных вычислений по меньшей мере первого фрагмента вычислительной задачи;по меньшей мере одно вспомогательное средство (B), размещенное для вычисления по меньшей мере второго фрагмента вычислительной задачи, при этом каждое вспомогательное средство (B) взаимодействует с инфраструктурой связи (IN); исредство управления ресурсами (RM), размещенное для назначения по меньшей мере одного вспомогательного средства (B) по меньшей мере одному из множества вычислительных узлов (CN) для вычисления указанного второго фрагмента вычислительной задачи, при этом указанное назначение осуществляется в соответствии с заданным метрическим показателем назначения.2. Структура компьютерного кластера по п.1, характеризующаяся тем, что выполнена с ...

Technologien zur Durchführung einer Orchestrierung mit Online-Analyse von Telemetriedaten

Technologien zur Durchführung einer Orchestrierung mit Online-Analyse von Telemetriedaten umfassen einen Orchestrator-Server zum Zuweisen von Arbeitslasten an jeden aus einer Gruppe verwalteter Knoten, Empfangen von Telemetriedaten, die eine Ressourcennutzung anzeigen, von den verwalteten Knoten, wenn die Arbeitslasten ausgeführt werden, Erzeugen einer Datenanalyse in Abhängigkeit von den Telemetriedaten, wenn die Arbeitslasten ausgeführt werden, Bestimmen von Anpassungen der Arbeitslastzuweisungen in Abhängigkeit von der Datenanalyse, wenn die Arbeitslasten ausgeführt werden, um die Ressourcennutzung unter den verwalteten Knoten zu erhöhen, und Anwenden der bestimmten Anpassungen auf die verwalteten Knoten, wenn die Arbeitslasten ausgeführt werden. Außerdem werden andere Ausführungsformen beschrieben und beansprucht.

Technologien zum Verwalten der Zuweisung von Beschleunigerressourcen

Technologien zum dynamischen Verwalten der Zuweisung von Beschleunigerressourcen enthalten einen Orchestrator-Server. Der Orchestrator-Server hat die Aufgabe, einem verwalteten Knoten eine Arbeitslast zur Ausführung zuweisen, einen vorhergesagten Bedarf für eine oder mehrere Beschleunigerressourcen zu bestimmen, um die Ausführung eines oder mehrerer Jobs innerhalb der Arbeitslast zu beschleunigen, vor dem vorhergesagten Bedarf eine oder mehrere Beschleunigerressourcen bereitzustellen, um den einen oder die mehreren Jobs zu beschleunigen, und dem verwalteten Knoten die eine oder die mehreren bereitgestellten Beschleunigerressourcen zuzuweisen, um die Ausführung des einen oder der mehreren Jobs zu beschleunigen. Andere Ausführungsformen werden ebenfalls beschrieben und beansprucht.

Verfahren und System zum Optimieren des Platzierens virtueller Maschinen in Cloud-Computing-Umgebungen

Die Erfindung stellt ein Verfahren und ein System zum Optimieren des Platzierens von Instanzen der Abbilder (103) virtueller Maschinen in einer Cloud-Computing-Umgebung bereit. Das Verfahren umfasst die Schritte zum Empfangen einer Anforderung zum Nutzen einer neuen Instanz eines VM-Abbilds; Lesen von benutzerspezifischen und allgemeinen VM-Ressourcen-Nutzungsprofilen, die erste Ressourcen-Inanspruchnahmedaten umfassen; Lesen von Ressourcen-Poolprofilen, die zweite Ressourcen-Inanspruchnahmedaten umfassen; für jedes der Ressourcen-Poolprofile Analysieren und Angleichen des gelesenen VM-Ressourcen-Nutzungsprofils an die gelesenen Ressourcen-Poolprofile, Berechnen eines kumulierten Ressourcen-Inanspruchnahmeprofils und Ermitteln des einen der mehreren Ressourcen-Pools, der die geringste kumulierte Ressourcen-Inanspruchnahme aufweist.

Auswählen eines Hosts für eine virtuelle Maschine unter Verwendung einers Hardware-Multithreading-Parameters

Ein Cloud-Manager überwacht verfügbare Ressourcen auf Host-Computersystemen einschließlich einer Anzahl von Hardware-Threads, die durch CPUs auf den Host-Computersystemen unterstützt werden. Der Cloud-Manager empfängt eine Anforderung zum Bereitstellen einer virtuellen Maschine (VM), die einen Hardware-Multithreading-Parameter enthält, der das Ausmaß von Hardware-Multithreading angibt, das auf dem Host-Computersystem erforderlich ist. Der Cloud-Manager wählt anschließend ein Host-Computersystem für die VM aus und berücksichtigt hierbei den Hardware-Multithreading-Parameter.

Method and system for generating a view

A system for generating a view, e.g. a web page wherein a static first set of declarations in a metadata data model, e.g. a resource description framework (RDF) retrieved from a view definition are stored in storage of a computer system. A second non-static set of declarations in the metadata data model that are associated with the first set of declarations are also stored in the storage. At least one request for a set of requested data is resolved to a subset of the first set of declarations and the second set of declarations using semantic descriptions provided for the first and second sets of declarations and the requested data. A view rendered from the subset of the first set of declarations and the second set of declarations is updated whenever the second set of declarations is updated.

Method and system for managing data-sharing sessions

A method and computer system for managing data sharing sessions is provided which is resource efficient. The data-sharing session has a set of software systems participating therein. Requests are maintained for the software systems for sets of requested data. Values are stored for shared data items received from the software systems in the data-sharing session. The shared data items are resolved to at least one of the sets of the requested data using semantic descriptions provided for the shared data items and the requested data. The software systems requesting the at least one set of requested data are notified whenever updates to the values of the shared data items are available. The data-sharing session is destroyed if there is one of an absence of activity, an absence of one of the software systems having a particular characteristic in the data-sharing session, or a static value associated said data sharing session. The absence of activity may be an absence of updates or data items ...

Enabling control to a hypervisor in a cloud computing enviroment

Method and system of network transfer adaptive optimization in large-scale parallel computing system

Automatic selection of infrastructure on a hybrid cloud environment

Run-ahead approximated computations

Selecting a host for a virtual machine using hardware multithreading parameter

Job processing in quantum computing enabled cloud environments

A compatibility is ascertained between a configuration of a quantum processor (q-processor) of a quantum cloud compute node (QCCN) in a quantum cloud environment (QCE) and an operation requested in a first instruction in a portion (q-portion) of a job submitted to the QCE, the QCE including the QCCN and a conventional compute node (CCN), the CCN including a conventional processor configured for binary computations. In response to the ascertaining, a quantum instruction (q-instruction) is constructed corresponding to the first instruction. The q- instruction is executed using the q-processor of the QCCN to produce a quantum output signal (q-signal). The q-signal is transformed into a corresponding quantum computing result (q- result). A final result is returned to a submitting system that submitted the job, wherein the final result comprises the q-result.

Resource allocation method and system

A method and system for job scheduling in distributed data processing system with identification of optimal network topology

System and method for allocating computing resources for a grid virtual system

Instance usage facilitating system

Automatic diagonal scaling of workloads in a distributed computing environment

A method for automatic diagonal scaling of workloads in a distributed computing environment includes, for each of a plurality of resources of each of a plurality of application instances, a determination as to whether a change in allocation of at least one of the plurality of resources is required. Operations requirements are computed for each of the plurality of application instances, the computed requirements including vertical increase and decrease operations,and horizontal split and collapse operations. The vertical decrease and horizontal collapse operations are first processed, the vertical increase and horizontal split operations are ordered, and the vertical increase and horizontal split operations are subsequently processed based on the ordering, thereby optimizing application efficiency and utilization of the plurality of resources in the distributed computing environment.

A method and system for job scheduling in distributed data processing system with identification of optimal network topology

Spark-based imaging satellite task preprocessing parallelization method

Spark (RTM) based imaging satellite task preprocessing parallelization method includes: 101 performing orbit prediction parallelization design and decomposing a large-scale observation task into multiple small tasks, each small task being completed independently; and 102 implementing parallelized orbit prediction. Orbit prediction inputs of multiple satellites may be obtained, encapsulated into an RDD and output via an orbit prediction program. Elements in the RDD may be transmitted to the orbit prediction program by means of pipe. An output result from orbit prediction computing of each satellite in each computing time segment may be obtained and an orbit identification parameter may be used to distinguish between output results. Output results storage manner may be writing into a local file system, RDD or Redis (RTM) memory. Spark (RTM) cluster environment may be initialised and a cluster parameter may be configured. Preprocessing may be used in large‐scale satellite observation task ...

Elastic execution of machine learning workloads using application based profiling

GRID PARALLELAUSFÜHRUNG

PROCEDURE FOR THE SUPPLY OF AN APPLICATION OF GRID NETWORK WORKS OVER A TRANSPORTATION NETWORK

DISTRIBUTION OF DATENUND TASK INSTANCES IN LATTICE ENVIRONMENTS

FIREWALL PARALLEL PROCESSING PROTECTIVE SYSTEM IN A GLOBAL COMPUTER NETWORK ENVIRONMENT

Systems and methods for blueprint-based cloud management

Systems, methods, and media for translating requests to acquire or change goods and services by receiving a request in a service catalog. The received request is received in a format that is not suitable for a target vendor. The received request is then translated into a format suitable for the target vendor. The translated received request is then transmitted to the vendor using the translated format.

Connection leasing system and related methods for use with legacy virtual delivery appliances

A computing system may include client devices configured to request connections to virtual sessions using connection leases issued based upon published resource entitlements, and a computing device configured to store and update the published resource entitlements. The system may also include a virtual delivery appliance configured to provide the client devices with access to the virtual sessions based upon connection descriptor files. A connector appliance may be configured to receive connection requests from the client devices including the connection leases, request validation of the connection leases from the computing device, and resolve the connection leases to the virtual delivery appliance and return a session validation to the client devices responsive to validation of the connection leases. The client devices may be configured to generate the connection descriptor files responsive to the session validations, and initiate connections with the virtual delivery appliance using the ...

OPPORTUNISTIC RESOURCE MIGRATION TO OPTIMIZE RESOURCE PLACEMENT

A distributed system may implement opportunistic resource migration to optimize resource placement. Resources may be placed amongst different resource hosts of a distributed 5 system. An evaluation of the current placement may be performed according placement criteria that improve placement of the resources at the distributed system. Based on the evaluation, the prospective migration of resources that exceed an improvement threshold may be identified as candidate resources to migrate. Migration for the candidate resources may be opportunistically performed. In some embodiments, a priority may be assigned to the candidate resources 0 according to which the candidate resources are selected for performing migration.

Interconnection platform for real-time configuration and management of a cloud-based services exchange

In one example, a cloud-based services exchange comprises a plurality of interconnection assets configured to connect a customer of the cloud-based services exchange to one or more cloud service providers, the plurality of interconnection assets including a virtual circuit by which the 5 customer accesses a cloud service from the one or more cloud service providers; and an orchestration engine configured to modify the plurality of interconnection assets.

Auto-scaling hosted machine learning models for production inference

Techniques for auto-scaling hosted machine learning models for production inference are described. A machine learning model can be deployed in a hosted environment such that the infrastructure supporting the machine learning model scales dynamically with demand so that performance is not impacted. The model can be auto-scaled using reactive techniques or predictive techniques.

Dynamic migration within a network storage system

This is directed to providing access to content stored on a personal cloud. In particular, a personal cloud can be constructed by sharing the resources of several devices owned by a user and by other users trusted by the user. To add a device to a personal cloud, the device can identify its owner to a librarian, which can provide addressing information for other devices forming a cloud on behalf of the owner. The new device can establish a communications path with the other devices, and configure itself based on the services or data required for the personal cloud (e.g., as determined from communications with the other devices). Services operating on individual devices of the personal cloud can migrate dynamically and automatically to ensure that a user can remove a device from the personal cloud at will without adversely affecting the operation of the personal cloud.

Availability management for reference data services

Various aspects for scaling an availability of information are disclosed. In one aspect, a response performance associated with responding to data consumption requests is monitored. A characterization of the response performance is ascertained, and a scaling of resources is facilitated based on the characterization. In another aspect, a data consumption status indicative of data consumed is ascertained. Here, a scalability interface is provided, which displays aspects of the status, and receives an input from a content provider. An allocation of resources is then modified in response to the input. In yet another aspect, a response performance associated with responding to data consumption requests is monitored. An application programming interface (API) call is generated based on a characterization of the response performance, and transmitted to a content provider. An API response is then received from the content provider indicating whether a scaling of resources for hosting the data was ...

Method and apparatus for controlling an extensible computing system

DISTRIBUTED COMPUTER

Virtual machine migration tool

A method of migrating applications to an application hosting cloud that hosts any applications for access by clients over the Internet, the method comprising: selecting a target application to migrate to the application hosting cloud, the application hosting cloud providing cloud-based virtual platforms wherein applications can execute as if on a hardware platform, the target application, prior to migration, configured to execute on a particular computer host platform; passing the target application to a migration tool, wherein the migration tool is provided with access to a rules library comprising one or more pluralities of migration rules, wherein each plurality of migration rules corresponds to a respective different application hosting cloud, and wherein each plurality of migration rules describes at least one of code rules, operating system rules, semantics rules, database rules, or installer rules; parsing and analyzing source files and configuration files of the target application ...

MULTI-CLOUD NETWORK PROXY FOR CONTROL AND NORMALIZATION OF TAGGING DATA

A system including a communication interface operable to establish a data connection with a target virtual hosting platform, a primary metadata tagging repository for technical components hosted by the target virtual hosting platform, the metadata tagging repository including a metadata tag identifier set, and a metadata tag content set linked to the metadata tag identifier set, proxy circuitry coupled to the communication interface and the metadata tagging repository, the proxy circuitry configured to make a determination of whether the target virtual hosting platform provides native metadata tagging capability, proxy metadata tag identifiers to the metadata tag identifier set in the primary metadata tagging repository, proxy metadata tag content to the metadata tag content set in the primary metadata tagging repository, and synchronize the metadata tag identifiers and metadata tag content, when the determination is that the target virtual hosting platform provides native metadata tagging ...

SPRINT: A SMART PRINTING DEVICE

SPRINT: A SMART PRINTING DEVICE Abstract: In today's world, long lines are one of the very few things that can put a stop to the fast paced urban lifestyle. But the truth is, in India, more often than not, people do not bother with queuing up and prefer mobs. Our project, SPRINT is an attempt to reduce the need for long lines in one of the very basic services provided within any institute - printing out documents. Every single student has to face the hassle of waiting in long lines. Moreover, due to a printer traditionally requiring wired connection with a network or a system, there are currently only a few locations where paid printing service is feasible. SPRINT is an attempt to simplify and speed up the process of providing paid printing services to anyone within the campus by utilizing a simple cloud based website, aided by a Raspberry Pi. From the website, a customer can upload his pdf document to be printed into the server, which will prompt him to make the appropriate payment based ...

Method and system for Load Balancing in Computational Grid

The present disclosure relates to a method for load balancing in computational grid using activity-based and CPU usage approach. The objective of the present disclosure is to reduce the execution time of application for completion of particular task. Dynamic Load Balancing algorithm is used for matrix user which aims to execute their program speedily using minimum execution time and minimize the idle time of processors. When system performing task and in between system fail then machine of load transfer from one machine to another machine. Load Balancing calculation and proposed an upgraded calculation which all the more effectively actualizes three out of five strategies executed in the existing load balancing calculation. CoL 'Ii 13J aia F 09 R- -0 C: ai V IA- Ln C: 73 03 -F- : o~j 130 :3:- ~ i r 03 C Cn .9 r3 ...

SYSTEM AND METHOD OF PROVIDING RESERVATION MASKS WITHIN A COMPUTE ENVIRONMENT

SYSTEM AND METHOD OF CO-ALLOCATING A RESERVATION SPANNING DIFFERENT COMPUTE RESOURCES TYPES

... ²²²A system and method of co-allocating resources within a compute environment ²are disclosed. The method embodiment of the invention comprises receiving a ²request for a reservation for a first type of resource, analyzing constraints ²and guarantees associated with the first type of resource, identifying a first ²group of resources that meet the request for the first type of resource and ²storing in a first list, receiving a request for a reservation for a second ²type of resource, analyzing constraints and guarantees associated with the ²second type of resource, identifying a second group of resources that meet the ²request for the second type of resource and storing in a second list, ²calculating a co-allocation parameter between the first group of resources and ²the second group of resources and reserving resources according to the ²calculated co-allocation parameter of the first group of resources and the ²second group of resources. The request may also request exclusivity of the ²reservation ...

FACILITATING ACCESS TO INPUT/OUTPUT RESOURCES VIA AN I/O PARTITION SHARED BY MULTIPLE CONSUMER PARTITIONS

... ²²²At least one input/output (I/O) firmware partition is provided in a ²partitioned environment to facilitate access to I/O resources owned by the at ²least one I/O firmware partition. The I/O resources of an I/0 firmware ²partition are shared by one or more other partitions of the en~vironment, ²referred to as consumer partitions. The consumer partitions use the I/O ²firmware partition to access the I/O resources. Since the I/O firmware ²partitions are responsible for providing access to the I/O resources owned by ²those partitions, the consumer partitions are relieved of this task, reducing ²complexity and costs in the consumer partitions.² ...

SYSTEM AND METHOD FOR ENFORCING NETWORK DEVICE PROVISIONING POLICY

Systems and methods are provided for enforcing a network device provisioning policy. In one embodiment, a method may employ a computer based system to restrict access to data center resources, receive provisioning requests for access to the data center resources, authorize the provisioning requests after compliance with the network provisioning policy and allow the network device to access authorized data center resources. In another embodiment, a system includes interfaces for provisioning policy, request and task status information. The information provided by these interfaces is then used to determine compliance with applicable network device provisioning policies and restrict or allow access to the data center resources according to the provisioning policy.

MANAGING COMPONENT PROGRAMS WITHIN A SERVICE APPLICATION

Methods, systems, and computer-storage media having computer- executable instructions embodied thereon that, when executed, perform methods in accordance with embodiments hereof, for managing component programs within a service application according to a service model. Initially, configuration settings, which can be administered to the component programs, are extracted from the service model. An instantiation process is initiated to manage the service application in accordance with the changes to a level of load on the service application and/or to specifications within the service model. The instantiation process includes deploying, or identifying as available, the component programs within the data center, and automatically propagating formalized values derived from the configuration settings throughout the deployed component programs. These derived formalized values are installed into the component programs, thereby providing for functionality of the service application consistent with ...

METHOD AND SYSTEM FOR A GRID-ENABLED VIRTUAL MACHINE WITH MOVABLE OBJECTS

A method, an apparatus, a computer program product, and a data processing system provide for operation of a virtual machine with embedded functionality for interoperating with other virtual machines in a computational grid. A plurality of virtual machines are run on one or more devices within a data processing system; each virtual machine in the plurality of virtual machines incorporates functionality for interoperating and associating with other virtual machines in a virtual machine cluster in a grid-like manner. Each virtual machine in the virtual machine cluster acts as a node within the virtual machine cluster. A virtual machine manages its objects in association with an object group, and each virtual machine may manage multiple object groups. The virtual machines share information such that the object groups can be moved between virtual machines in the virtual machine cluster, thereby allowing the virtual machine cluster to act as one logical virtual machine.

EXTENSIBLE COMPUTING SYSTEM

Methods and apparatus providing a dynamically sized, highly scalable and available server farm are disclosed. A Virtual Server Farm (VSF) is created out of a wide scale computing fabric ("Computing Grid") which is physically constructed once and then logically divided up into VSFs for various organizations on demand. Each organization retains independent administrative control of a VSF. A VSF is dynamically firewalled within the Computing Grid. An allocation and control of the elements in the VSF is performed by a Control Plane connected to all computing, networking, and storage elements in the computing grid through special control ports. The internal topology of each VSF is under control of the Control Plane. No physical rewiring is necessary in order to construct VSFs in many different configurations, including single- tier Web server or multi-tier Web-server, application server, database server configurations. Each tier of a multi-tier VSF (e.g. Web server tier, application server tier ...

GLOBAL NETWORK COMPUTERS

Advantage is taken of the processing power of idle PCs (slaves) to process a complex and time consuming task. A master PC subdivides the task into a plurality of parts and sends the parts to the appropriate slaves. The PCs can alternate between functioning as a master and as a slave. The master is protected by a firewall. Every PC has a signalling device to indicate the PCs availability for using its processing power. The flow of computing power between the slaves and the network is monitored, so as to arrive at a net cost basis for every PC.

GRID SERVICE SCHEDULING OF RELATED SERVICES USING HEURISTICS

A method and system for creating service instances in a computing grid. The method can include scheduling a service (200B) in the computing grid (120) to process at least a portion of a requested transaction. At least one additional service related to the scheduled service can be identified, and a load condition can be assessed in the at least one additional service related to the scheduled service. A new instance of the at least one additional service can be created (260) if the load condition exceeds a threshold load. In this way, an enhanced capacity for processing transactions can be established in the related services in advance of a predicted increase in load in the grid.

SYSTEM AND METHOD FOR PROVIDING OBJECT TRIGGERS

The present invention provides for systems and methods of dynamically controlling a cluster or grid environment. The method comprises attaching a trigger to an object and firing the trigger based on a trigger attribute. The cluster environment is modified by actions initiated when the trigger is fired. Each trigger has trigger attributes that govern when it is fired and actions it will take. The use of triggers enables a cluster environment to dynamically be modified with arbitrary actions to accommodate needs of arbitrary objects. Example objects include a compute node, compute resources, a cluster, groups of users, user credentials, jobs, resources managers, peer services and the like.

CLOUD RESOURCE PROVISIONING USING BLUEPRINT CHAINING

A system and method including organizing blueprints into a blueprint chain, the blueprint chain connecting the blueprints in an order, wherein a blueprint in the blueprint chain includes resources connected to form a schematic of a portion of an application, wherein a first resource of the blueprint is associated with a first provider and a second resource of the blueprint is associated with a second provider, identifying at least one cloud account suitable for provisioning the blueprint chain, wherein the at least one cloud account includes the first provider and the second provider, and generating an orchestration to provision an instance of the application, the orchestration including a plurality of provisioning steps based on the blueprint chain and a selected one of the at least one cloud account, wherein an ordering of the plurality of provisioning steps depends on the order of the blueprints in the blueprint chain.

SYSTEMS AND METHODS FOR PRIVATE CLOUD COMPUTING

A system and method are disclosed for private cloud computing and for the development and deployment of cloud applications in the private cloud. The private cloud computing system and method of the present invention include as components at least a cloud controller, a cloud stack, Service Registry, and a cloud application builder.

DATA PROCESSING METHOD AND RELATED PRODUCTS

The present disclosure discloses a data processing method and related products, in which the data processing method includes: generating, by a general-purpose processor, a binary instruction according to device information of an AI processor, and generating an AI learning task according to the binary instruction; transmitting, by the general-purpose processor, the AI learning task to the cloud AI processor for running; receiving, by the general-purpose processor, a running result corresponding to the AI learning task; and determining, by the general-purpose processor, an offline running file according to the running result, where the offline running file is generated according to the device information of the AI processor and the binary instruction when the running result satisfies a preset requirement. By implementing the present disclosure, the debugging between the AI algorithm model and the AI processor can be achieved in advance.

MANAGING EXECUTION OF DATA PROCESSING JOBS IN A VIRTUAL COMPUTING ENVIRONMENT

A device may receive a job request associated with a data processing job, including job timing data specifying a time at which the data processing job is to be executed by a virtual computing environment. The device may receive user data associated with the job request and validate the data processing job based on the user data. In addition, the device may identify a priority associated with the data processing job, based on the user data and the job timing data. The device may provide, to a job queue, job data that corresponds to the data processing job, and monitor the virtual computing environment to determine when virtual resources are available. The device may also determine, based on the monitoring, that a virtual resource is available and, based on the determination and the priority, provide the virtual resource with data that causes execution of the data processing job.

SYSTEMS AND METHODS FOR ON- DEMAND DEPLOYMENT OF SOFTWARE BUILD AND TEST ENVIRONMENTS

Systems (100) and methods are described that allow for the dynamic allocation and re-allocation of hardware and software resources (106-226) to support the build, integration, and test phases of complex software development projects. The invention provides customers who have medium to large development teams, which may be geographically distributed, with an integrated development environment, which includes centralized governance of software code repositories, build systems and test systems. Embodiments of the invention include a centralized, scalable, and dynamic system architecture which allows customers to (1) replicate the internal build, integrate, and test environments that were previously used on the customer premises, (2) provision and re-provision such resources on demand, and (3) seamlessly integrate their internal environments with the system described herein.

APPLICATION PLATFORM OPERABLE ON NETWORK NODE

A formula-driven programming-environment is described, which may be used to provide an environment for applications to operate within a network node or other computing device. In one example, statements of a program may be interpreted to thereby execute formula-style commands within an address space defined and constrained in a memory device by the integrated development environment. The commands may obtain data, assign values to variables and access data from other node(s) by the interpretation of statements in the program and communicating over a network. The communicating may include queuing a message for transmission by the formula-driven programming-environment. The commands may provide named access or relative access to data in response to the interpretation of statements in the program. The commands may communicate with at least one application located on a remote computing device in response to the interpretation of statements in the program.

EXECUTING COMMANDS WITHIN VIRTUAL MACHINE INSTANCES

Technologies are disclosed herein for executing commands within virtual machine ("VM") instances. A public web service application programming interface ("API") is exposed within a service provider network that includes methods relating to the execution of commands within VM instances. For example, the API might include a method for obtaining a list of the commands that can be executed within a VM instance. The API might also include a method for requesting the execution of a command within a VM instance. The API might also include a method for requesting data describing the status of the execution of a command within a VM instance. The API might also expose other methods. A software agent executing on a VM instance may be utilized to provide a list of commands that can be executed in the VM, to execute requested commands, and to provide data describing the status of execution of a command.

METHOD AND SYSTEM FOR GENERATING A VIEW

A method and system for generating a view is provided. A first set of declarations in a metadata data model retrieved from a view definition are stored in storage of a computer system. The first set of declarations are static. A second set of declarations in the metadata data model that are associated with the first set of declarations are stored in the storage. At least one request for a set of requested data is resolved to a subset of the first set of declarations and the second set of declarations using semantic descriptions provided for the first and second sets of declarations and the requested data. A view rendered from the subset of the first set of declarations and the second set of declarations is updated whenever the second set of declarations is updated.

VIRTUAL SERVER CONTROL SYSTEM AND PROGRAM

The present invention provides technology capable of ensuring sufficient effects, such as processing efficiency and load distribution, and the feasibility of a system/service, in regards to scale control for a virtual server or such in a target system for a public cloud or such. This system has functionality to perform scale control of a virtual server (21) in a target system (2), and has the following: a processing unit (14) that sets calendar information (51) for a customer company that uses the target system (2) and sets definition information (52) for generating an actual schedule for scale control; a processing unit (11) that references the configuration information (51, 52) to perform scheduling processing that generates actual schedule information (53) for scale control; and a processing unit (12) that performs processing to send scale control instructions to the virtual server (21) on dates that are in accordance with the actual schedule information (53).

Migration of applications between an enterprise-based network and a multi-tenant network

The operation of the industrial assets processing from the analysis of the data example of the operation of the distributed cache

DISTRIBUTED DATA SET INDEXING

PROCESS OF MANAGEMENT OPTIMISEE OF COMPUTER'S RESOURCES DISTRIBUEES

METHOD FOR AUTOMATIC BACKUP AND MAINTENANCE DATA OBTAINED BY SERVICES WITH STATE UPON INITIATION OF A SERVICE WITHOUT STATE IN A SYSTEM OPERATING IN A CLOUD

SCHEDULING METHOD OF SPOTS AT THE NODES OF A COMPUTER CLUSTER, CLUSTER RELATED TASK SCHEDULER AND

L'invention concerne une méthode d'ordonnancement de tâches, au niveau d'au moins certains nœuds (1) d'un cluster informatique, comprenant : d'abord, le lancement (22) de deux containers (5, 8) sur chacun desdits nœuds (1), un container standard (5) et un container prioritaire (8), ensuite, pour tout ou partie desdits nœuds (1) à deux containers (5, 8), au niveau de chaque nœud (1), tant qu'une tâche prioritaire ne survient pas, l'affectation de ou des ressources disponibles du nœud (1) à son container standard (5) pour exécuter une tâche standard, son container prioritaire (8) n'exécutant pas de tâche, lorsqu'une tâche prioritaire survient, le basculement (25) dynamique d'une partie seulement des ressources de son container standard (5) vers son container prioritaire (8), de manière à ce que, d'une part la tâche prioritaire soit exécutée dans le container prioritaire (8) avec la partie basculée des ressources, et d'autre part la tâche standard continue d'être exécutée, sans être arrêtée ...

METHOD AND DEVICES FOR FORMING A CLOUD COMPUTER STORING THE RESULT OF EXECUTION OF A TASK COMPUTING OFFSET

ACCESSING COMPUTATIONAL GRIDS

클라우드 릴리즈 파이프라인들의 진단 및 최적화

... 사용자들에게, 사용자들의 애플리케이션의 개발 및 성능의 최적화하는 방법에 관한 권고 사항들을 제공할 수 있는 툴을 제공하기 위한 방법들 및 시스템들이 제공된다. 진단 및 최적화 방법, 시스템, 및 엔진은, 예를 들어, 사용자가 높은 릴리즈 생산성, 관리 편의, 및 비용 최적화를 최선으로 균형을 잡는 방법에 관하여 권고 사항들/제안들을 생성하기 위해 애플리케이션의 확립, 배치, 릴리즈, 및 실행과 연관된 다양한 데이터를 캡처하고, 이러한 데이터를 활용한다. 방법들 및 시스템들은, 예를 들어, 사용자가 이들의 애플리케이션 토폴로지를 상이하게 레이아웃하고, 레이턴시를 감소시키고, 데이터 데이터 로컬리티를 증가시키거나 또는 청구 비용들을 최적화할 수 있는 것을 포함하여 사용자가 이들의 시스템을 최적화할 수 있는 방법들에 관한 권고 사항들을 생성하기 위해서 (예를 들어, 사용자가 코드를 제출하는 시각부터 애플리케이션이 실제로 실행될 때까지) 사용자의 개발 프로세스의 엔드-투-엔드 스토리를 활용할 수 있다.

MOBILE TERMINAL FOR PROVIDING A MOBILE CLOUD SERVICE AND AN OPERATING METHOD FOR THE SAME

PURPOSE: A mobile terminal for providing a mobile cloud service is provided to offer a cloud service in a mobile environment. CONSTITUTION: A mobile cloud terminal platform(220) receives a cloud application by accessing to a mobile cloud server. The mobile cloud terminal platform offers a mobile cloud service using the cloud application. A local terminal platform(230) executes a local application built in the mobile terminal. An operating system(210) operates one of the mobile cloud terminal platform or the local terminal platform based on the user setting environment. COPYRIGHT KIPO 2011 ...

DYNAMIC LOAD BALANCING AND SCALING OF ALLOCATED CLOUD RESOURCES IN AN ENTERPRISE NETWORK

A SYSTEM AND METHOD FOR PERVASIVE COMPUTING

SYSTEM AND METHOD FOR DESCRIBING APPLICATIONS FOR MANAGEABILITY AND EFFICIENT SCALE-UP DEPLOYMENT

Connecting method for virtual machine in cloud system

A connecting method for virtual machines (VMs) in a cloud system mainly communicates with all switches in the cloud system though an agent network management service (ANMS) process. When a virtual machine (VM) is created in a physical machine (PM) in the cloud system, the ANMS process being aware that the VM is created and realizes the VM belonging to which virtual local area network (VLAN). The method uses the ANMS process to find a boundary point having a closest distance to the new-created VM, so as to acquire a shortest connecting route between the new-created VM and the boundary point. Finally, the ANMS process notifies all switches within the shortest connecting route to set their internal VLAN tag. Therefore, the new-created VM can connect to all VMs belonging to the same VLAN through the shortest connecting route.

Grid computing system, information processing unit, job execution request generation unit, control method, program, and recording medium

DELIVERY CONTROLLER BETWEEN CLOUD AND ENTERPRISE

A delivery controller for use in an enterprise environment that communicates with a cloud computing environment that is providing a service for the enterprise. As the cloud service processing progresses, some cloud service data is transferred from the cloud computing environment to the enterprise environment, and vice versa. The cloud service data may be exchanged over any one of a number of different types of communication channels. The delivery controller selects which communication channel to use to transfer specific data, depending on enterprise policy. Such policy might consider any business goals of the enterprise, and may be applied at the application level.

SCENARIO STATE PROCESSING SYSTEMS AND METHODS FOR OPERATION WITHIN A GRID COMPUTING ENVIRONMENT

Systems and methods are provided for generating multiple system state projections for one or more scenarios using a grid computing environment. A central coordinator software component executes on a root data processor and provides commands and data to a plurality of node coordinator software components. A node coordinator software component manages threads which execute on its associated node data processor and which perform a set of matrix operations. Stochastic simulations use results of the matrix operations to generate multiple state projections. Additional processing can be performed by the grid computing environment based upon the generated state projections, such as to develop risk information for users.

METHOD FOR REMEMBERING RESOURCE ALLOCATION IN GRIDS

A grid manager manages numerous submissions of a job request in view of maintaining a high degree of performance continuity in the execution of the numerous submissions of the job request by one or more job handlers. To this end, the grid manager receives an initial submission of the job request specifying one or more resource selection parameters, and selects one or more job handlers for executing the initial submission of the job request based on the specified resource selection parameter(s). To facilitate a high degree of performance continuity in the execution of a resubmission of the job request, the grid manager assigns a job request identification corresponding to a resource selection parameter compilation including the specified resource selection parameter(s) as well as each resource selection parameter unspecified in the job request that facilitates a selection of one or more job handlers for executing the resubmission of the job request.

SYSTEM FOR THE DISTRIBUTED MANAGEMENT OF COMPUTER RESOURCES AND CALCULATIONS

The invention relates to a system for the distributed management of computer resources and calculations, comprising a network that connects active or idle machines. The inventive system can be used for the resolution of tasks, whereby all of said tasks constitute a single problem that is to be solved and one task is executed by one of the active machines in the network using application software (22a). The system is characterised in that each machine in the system comprises: a means for selecting at least one network address (21b) corresponding to another machine in the system; a computer means for managing the computer resources (20), including, among others, a means for updating task state information, said information being conveyed through the network by means of a message (4); and a random task selection means. In addition, the active machines also comprise the application software (22a) and data (23a) which are used to solve the problem.

GOAL-ORIENTED PREDICTIVE SCHEDULING IN A GRID ENVIRONMENT

A method for scheduling jobs in a networked computing grid is described. The method includes scheduling jobs to meet goals related to execution of the jobs within the computing grid. The jobs maybe scheduled by evaluating job execution goals against available resource slots provided by the computing grid. Also disclosed are related methods for scheduling jobs in which the jobs are submitted to service classes having defined job execution goals, and wherein the jobs are scheduled according to the job execution goals of the service classes.

METHOD AND APPARATUS FOR CAPACITY PLANNING AND RESOURCE AVAILABILITY NOTIFICATION ON A HOSTED GRID

A computer implemented method, apparatus and computer usable program code for dynamically changing allocation policy in a host grid to support a local grid. The host grid is operated according to a set of allocation policies. The set of allocation policies corresponds to a predetermined resource allocation relationship between the host grid and a local grid. Based on the set of allocation policies, at least one resource on the host grid is allocated to the local grid. A monitoring agent is then used to monitor one of the local grid and both the local grid and the host grid for a change in a parameter. A change in the parameter may result in a change in the set of allocation policies.

PARALLEL COMPUTING SYSTEM, METHOD AND ARCHITECTURE

A parallel or computing system and method make use of a plurality of adapters each affording a specific type of processing algorithm (10a and 10b). At each point in an application, an adapter is identified, to parallelize that portion of the application. The process involves associating an appropriate adapter with the application portion, parsing the application portion to define tasks that may be distributed over the available computers. Combined with the parallelized program is a software server (22) that is designed to cooperate with the adapters to control and supervise distributed processing functions. Such functions include mapping, load balancing, and error detection and correction. Also included are functions that cause the results of the computing to be coordinated in real-time and returned appropriately, according to the application. In addition to the parallelized program and server, an application created by the present invention is provided with the functionality of virtual ...

RECOMMENDATION ENGINE FOR APPLICATION PROGRAMMING INTERFACE (API) IN A MULTI-CLOUD ENVIRONMENT

The multiplicity of APIs that existing in a multi-cloud environment creates significant complexity for users. It can be unclear which API call should be made for a specific layer. Also, given the different API calls used by different cloud providers, they can be easily confused. Accordingly, embodiments help to reduce this complexity and simplify multi-cloud environments from a developer/user perspective. In one or more embodiments, an API with an error and its error message are captured and used as context-based information to suggest one or more recommendations to a user about how their API call should be made (e.g., to another API, to an alternative cloud provider, or by changing syntax). 1. A computer-implemented method for recommending an application programming interface (API) query , the method comprising:intercepting an error message related to an API query that includes an error that results in the error message being generated following an attempt to execute the API query; using the identified field in the error message to search an API datastore for possible API matches as potential recommendations; and', 'using at least one or more of the non-identified fields in the error message to search the API datastore for possible API matches as potential recommendations;, 'responsive to the error message for the API query identifying a field within the API query that contains the error, performing at least one ofresponsive to the error message for the API query not identifying a field within the API query that contains the error, using one or more fields of the API query to search the API datastore for possible API matches as potential recommendations;supplementing the error message with a set of API recommendations from the potential recommendations; andsending the supplemented error message comprising the set of API recommendations for displaying to a user.2. The computer-implemented method of wherein the set of API recommendations comprises an indicator that ...

System for managing web-based swipe module tool and software for scrolling and paging through content data and applications

A cloud-based computer system and architecture for managing and migrating through web-based content data and content applications from multiple content data sources or service providers in real time is disclosed. The cloud-based computing system and architecture of the present invention includes a log-in or master server that acts as a single point access and supports a single user interface. The single user interface is preferably an icon-based master web-page with a slide tool that allows a user to scroll or page through the content data and/or content applications from the multiple content data sources or service providers in real time from a logged in remote computer device.

Aggregation across cloud providers

A method and apparatus for aggregating cloud system resources is described. In one embodiment, the method includes receiving a request to start a cloud computing session. The method may also include determining a cloud computing system from among a plurality of cloud computing systems that satisfies the request. Furthermore, the method may include routing the request to the determined cloud computing system to initiate the cloud computing session.

System and method for topology-aware job scheduling and backfilling in an HPC environment

A method for job management in an HPC environment includes determining an unallocated subset from a plurality of HPC nodes, with each of the unallocated HPC nodes comprising an integrated fabric. An HPC job is selected from a job queue and executed using at least a portion of the unallocated subset of nodes.

METHOD AND APPARATUS FOR EVENT CORRELATION RELATED TO SERVICE IMPACT ANALYSIS IN A VIRTUALIZED ENVIRONMENT

A computer processor device provides a dependency tree representing (i) relationships among all the infrastructure elements in a computer system that are related to delivery of a service by a computer system, and (ii) how the infrastructure elements interact with each other in a delivery of said service, wherein a state of an infrastructure element is impacted only by states among its immediately dependent infrastructure elements of the dependency tree. The computer processor device determines the state of the service by checking current states of infrastructure elements in the dependency tree that immediately depend from the service.

Method and apparatus for incorporating an internet of things (IoT) service interface protocol layer in a node

A method and apparatus are described for incorporating an Internet of Things (IoT) service interface protocol layer in at least one node. The format of various IoT messages used to communicate over a service interface are also described. A set of IoT service level operations may be defined in the node. The IoT service level operations may be performed on IoT information elements (IEs). The IoT service level operations may be defined in terms of various actions that are generic and applicable across industry verticals. The operations may leverage each other as sub-operations, (e.g., collaborate, share, synchronize, discover, associate, collect, aggregate, concatenate, share, relocate, invoke, delegate or surrogate). The IoT IEs may include at least one of a content IoT IE, a context IoT IE, a policy IoT IE, a decision IoT IE, an event IoT IE, a discovery IoT IE or a descriptor IoT IE.

Mechanisms for programmable composition of factor graphs

A computer-implemented method of deploying a cloud application comprises accessing, by one or more processors, a first factor graph that represents a first component of the cloud application, the first factor graph comprising a first set of nodes; accessing a second factor graph that represents a second component of the cloud application, the second factor graph comprising a second set of nodes; determining a third set of nodes that are present in both the first set of nodes and the second set of nodes; joining, by the one or more processors, the first factor graph and the second factor graph into a third factor graph, wherein the joining includes unifying the third set of nodes in the first factor graph and the second factor graph; based on the third factor graph, selecting computing resources; and deploying at least a portion of the cloud application to the selected computing resources.

Grid computing systems and methods thereof

A grid computing system, method, and computer program product, adapted to execute at least one workflow having a set of predefined operating parameters and including an execution module comprising a plurality of devices having a plurality of heterogeneous resources, wherein the plurality of devices is adapted to execute the at least one job by integrating the plurality of heterogeneous resources. The system further includes at least one grid workflow module. The grid workflow module includes a graphical user interface to provide at least one user to initiate and manage the at least one workflow based on the set of predefined operating parameters and the plurality of heterogeneous resources. Furthermore, the grid workflow module includes a manager module adapted to partition the at least one workflow into multiple jobs prior to the execution of the at least one workflow.

Dynamic processor redistribution between partitions in a computing system

A method, apparatus and program product for the dynamic reallocation of shared processing resources in a computing system is provided. The method/apparatus/program product attempts to allocate the shared processing resource among the two or more logical partitions in the computing system based on a current utilization of the shared processing resource among each of the two or more logical partitions and a current utilization of shared processing resource for the computing system as a whole. More specifically, the shared processing resource is reallocated from logical partitions having a relatively lower current utilization of their owned portion of the shared processing resource to logical partitions having a relatively high current utilization of their owned portion of the shared processing resource.

Mobile device workload management for cloud computing using SIP and presence to control workload and method thereof

A method is implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions. The programming instructions are operable to manage workload for cloud computing by transferring workload to at least one mobile device using Session Initiation Protocol (SIP).

Enhanced storage quota management for cloud computing systems

An embodiment of the invention provides a method for storage management in a cloud computing system. More specifically, locations of storage components in the cloud computing system and storage properties of the storage components are identified. The storage properties include the amount of available storage space and/or the cost of storage space. A storage quota for a user of the cloud computing system is generated with a cloud quota management module based on the locations of the storage components and/or the storage properties of the storage components. In at least one embodiment, the storage quota includes the maximum amount of storage allocated to the user in at least one of the storage components.

SYSTEMS AND METHODS FOR PERFORMING A TECHNICAL RECOVERY IN A CLOUD ENVIRONMENT

A computer-implemented method for testing failover may include: determining one or more cross-regional dependencies and traffic flow of an application in a first region of a cloud environment, wherein the one or more cross-regional dependencies include a dependency of the application in the first region of the cloud environment to one or more applications in at least one other region of the cloud environment; determining a risk score associated with performing failover of the application to a second region of the cloud environment at least based on the determined one or more cross-regional dependencies and traffic flow of the application; comparing the determined risk score with a predetermined risk score; in response to determining that the determined risk score is lower than the predetermined risk score, performing failover of the application to the second region of the cloud environment; isolating the second region of the cloud environment from the first region of the cloud environment ...

HYBRID CLOUD DELIVERY TELEMETRY ENGINE

Hybrid cloud delivery telemetry engines are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for hybrid cloud delivery telemetry may include: (1) receiving, at a user portal, a user identifier, wherein the user identifier is associated with a set of entitlements for patterns, resources, and services to which the user is authorized to access; (2) retrieving based on the user identifier, a pattern, a resource, and a service available to the user based on the user identifier; (3) presenting the available pattern, resource, and service to the user for selection; (4) receiving, at the user portal, a selection of at least one of the pattern, the resource, and the service from the user; and (5) provisioning a user-specific system based on the selection of at least one of the pattern, the resource, and the service.

Call Chain-Based Concurrency Control Method and Apparatus, and Control Node

A control node could obtain analysis statistical data of each of the multiple service nodes; determine a target service node with an inappropriate concurrency threshold according to the analysis statistical data of each service node; obtain a concurrency threshold of the target service node, and a concurrency threshold and weight information of a neighboring service node of the target service node; determine an updated concurrency threshold of the target service node according to the concurrency threshold of the target service node, the analysis statistical data, and the concurrency threshold and the weight information of the neighboring service node of the target service node; and send a concurrency threshold adjustment request to the target service node.

Media content rendering method, user equipment, and system

The present disclosure discloses a media content rendering method. The method is applied in a user equipment (UE) in a rendering system. The method includes determining, according to a rendering requirement of to-be-rendered media content, that a part of the to-be-rendered media content is to be rendered by a cloud device; sending, to the cloud device, a rendering indication message and first media content that needs to be rendered by the cloud device, where the rendering indication message is used to instruct the cloud device to render the first media content; and receiving a cloud processing result returned by the cloud device for the first media content. The UE can perform collaboratively rendering with the cloud device for the to-be-rendered media content, so that rendering resources of the UE and the cloud device are effectively used, and media content rendering efficiency is improved.

Resource prediction for cloud computing

The invention relates to a method for predicting an allocation of processing resources provided by a cloud computing module (230) to process a data set based on a predefined processing task. Input parameters are detected, the input parameters containing information about at least the data set to be processed by the cloud computing module and the processing task to be carried out on the data set. A model is selected from a plurality of different models provided in a model database (130), each model providing a relationship between the data set processing task and a predicted allocation of the processing resources. The allocation of the processing resources is predicted based on the selected model and based on the input parameters.

Availability management for reference data services

Various aspects for scaling an availability of information are disclosed. In one aspect, a response performance associated with responding to data consumption requests is monitored. A characterization of the response performance is ascertained, and a scaling of resources is facilitated based on the characterization. In another aspect, a data consumption status indicative of data consumed is ascertained. Here, a scalability interface is provided, which displays aspects of the status, and receives an input from a content provider. An allocation of resources is then modified in response to the input. In yet another aspect, a response performance associated with responding to data consumption requests is monitored. An application programming interface (API) call is generated based on a characterization of the response performance, and transmitted to a content provider. An API response is then received from the content provider indicating whether a scaling of resources for hosting the data was performed.

Service linkage system and information processing system

An object of the present invention is to enhance the followability of the automatic scaling of a whole system corresponding to an increase of requests in a service linkage system for linking plural services. A cloud that executes intermediate service receives an estimate of the output of service at a previous stage by an output rate estimating unit and an information gathering response from a cloud management server, estimates an output rate, and outputs the estimate to service at a following stage. A scaling control unit receives the estimate of the output of the service at the previous stage and the information gathering response, determines resources allocated to the intermediate service, and outputs a scaling request to the cloud management server and the output rate estimating unit.

Cloud-Processing Management With A Landscape Directory

Disclosed are methods, systems, apparatus and products, including a method that includes maintaining data in a cloud landscape directory, including data regarding multiple individual landscapes. Each landscape of the multiple individual landscapes identifying at least a set of applications, the set of applications of at least one of the multiple individual landscapes including at least one cloud-based application available for cloud-processing. The at least one cloud-based application is associated with the at least one of the multiple individual landscapes and is available for access and use. The method also includes processing at least one of a plurality of service requests based, at least in part, on the data regarding the multiple individual landscapes maintained in the cloud landscape directory.

Systems and methods for brokering optimized resource supply costs in host cloud-based network using predictive workloads

Embodiments relate to systems and methods for brokering optimized resource supply costs in a host cloud-based network using predictive workloads. In aspects, a set of usage histories can store patterns for users in a host cloud-based network recording the consumption of processor, memory, storage, operating system, application, or other resources subscribed to by the user. The operator of the cloud management system hosting the workloads of one or more users can track the aggregate user histories reflecting those workloads, and analyze them in terms of different time periods over which demands for resources may intensity or relax. The cloud management system can examine those workload patterns, and generate a set of predictively re-assigned workloads to be supported by different sets of resource servers during offpeak and/or other periods. The workload realignment to different resource servers can permit the operator of the cloud management system and/or other cloud provider to realize cost savings or other benefits by procuring resources on a predictive basis.

Negotiation tool and method for cloud infrastructure data sharing

A system and method are provided for data sharing. A sharing negotiation tool permits at least one consumer application to negotiate a service level agreement on a dataset which is being shared by a tenant application on a cloud. A capacity planner is configured to determine an appropriate allocation of cloud resources to ensure that the service level agreement of the at least one consumer application is satisfied.

Techniques for provisioning cloud computing environment resources based on social media analysis

A technique for provisioning computing environment resources based on social media analysis includes monitoring, using a data processing system, references (e.g., hyperlinks) provided by a first website to detect an anticipated flash crowd for a web-accessible resource (e.g., second website). The technique also includes generating, using the data processing system, a notice to allocate resources associated with the web-accessible resource to service the anticipated flash crowd.

Application-Based Specialization For Computing Nodes Within A Distributed Processing System

A distributed processing system is described that employs “application-based” specialization. In particular, the distributed processing system is constructed as a collection of computing nodes in which each computing node performs a particular processing role within the operation of the overall distributed processing system. Each of the computing nodes includes an operating system, such as the Linux operating system, and includes a plug-in software module to provide a distributed memory operating system that employs the role-based computing techniques. An administration node maintains a database that defines a plurality of application roles. Each role is associated with a software application, and specifies a set of software components necessary for execution of the software application. The administration node deploys the software components to the application nodes in accordance with the application roles associates with each of the application nodes.

Automated cloud workload management in a map-reduce environment

A computing device associated with a cloud computing environment identifies a first worker cloud computing device from a group of worker cloud computing devices with available resources sufficient to meet required resources for a highest-priority task associated with a computing job including a group of prioritized tasks. A determination is made as to whether an ownership conflict would result from an assignment of the highest-priority task to the first worker cloud computing device based upon ownership information associated with the computing job and ownership information associated with at least one other task assigned to the first worker cloud computing device. The highest-priority task is assigned to the first worker cloud computing device in response to determining that the ownership conflict would not result from the assignment of the highest-priority task to the first worker cloud computing device.

System and method for executing a cloud computing task

According to one embodiment system and method provides executing at least a portion of a cloud computing task on a client terminal. The system and method further includes checking whether the client terminal is recharging or not and accessing a server for executing the cloud computing task if the terminal is recharging.

Method to Dynamically Provision Additional Computer Resources to Handle Peak Database Workloads

A method to handle peak database workloads may include requesting resources, receiving virtual-machine information in response to the requesting, allocating first and second portions of a workload according to the virtual-machine information, processing the first portion on a virtual machine to generate a first result, creating a cloned virtual machine with a virtualization layer, and cloning with the virtualization layer a storage allocated to the virtual machine to create a cloned storage.

System and Method for Enforcing Future Policies in a Compute Environment

A disclosed system receives a request for resources, generates a credential map for each credential associated with the request, the credential map including a first type of resource mapping and a second type of resource mapping. The system generates a resource availability map, generates a first composite intersecting map that intersects the resource availability map with a first type of resource mapping of all the generated credential maps and generates a second composite intersecting map that intersects the resource availability map and a second type of resource mapping of all the generated credential maps. With the first and second composite intersecting maps, the system can allocate resources within the compute environment for the request based on at least one of the first composite intersecting map and the second composite intersecting map.

Apparatus, systems and methods for deployment and management of distributed computing systems and applications

Embodiments of apparatus, systems and methods facilitate the running a distributed computing application on at least one of a plurality of cloud infrastructures. In some embodiments, the processor implemented method comprises: deriving an infrastructure independent representation of the distributed computing application; and running the distributed computing application on one of a plurality of cloud infrastructures by utilizing a cloud-specific implementation of the infrastructure independent representation of the distributed computing application. The cloud-specific implementation of the infrastructure independent representation corresponds to the cloud infrastructure on which the distributed application is run.

Hybrid Cloud Workload Management

A method, apparatus, and computer program product for managing a workload in a hybrid cloud. It is determined whether first data processing resources processing a portion of a workload are overloaded. Responsive to a determination that the first data processing resources are overloaded, second data processing resources are automatically provisioned and the portion of the workload is automatically moved to the second data processing resources for processing. The second data processing resources are data processing resources that are provided as a service on the hybrid cloud. Processing of a first portion of a workload being processed on first data processing resources of a hybrid cloud are monitored simultaneously with monitoring processing of a second portion of the workload being processed on second data processing resources of the hybrid cloud. The workload may be allocated automatically between the first portion and the second portion responsive to the simultaneous monitoring.

System and method for managing a computing cluster

A method and system for managing a computing cluster including hosting a plurality of machines in a networked computing cluster, wherein the plurality of machines include service instances running on hosts, where the services have configured machine state; and wherein machine state includes configuration data and software of the machine; integrating the plurality of machines of the cluster with at least one configuration controller component; and the at least one configuration controller component, altering the machine state of at least one service instance.

Tier-based Dynamic Incentive Arbitration in an On-Demand Computing Environment

A system for allocating resources which are anticipated to be available in an on-demand computing at some time in the future, wherein a producer trending agent (PTA) lists resources according to a trend prediction of resource availability in the past, a consumer trending agent (CTA) places bids for listed resources according to previous resource usage trends, and an arbitration system (REAS) matches the bids with the listings to determine if a match exists. If so, a binding contract for consumption of the matched listed resources is established. The PTA also produce tier-based dynamic incentive (TDI) schema which divides potential bidders into tiers, and offers additional resource incentives according to the tiers. Both PTA and CTA dynamically update their available/usage trends, listings and bids, over time.

Systems and methods for generating marketplace brokerage exchange of excess subscribed resources using dynamic subscription periods

Embodiments relate to systems and methods for generating a marketplace brokerage exchange of excess subscribed resources using dynamic subscription periods. A set of aggregate usage history data can record consumption of processor, software, or other resources subscribed to by a set of users, in one cloud or across multiple clouds. An entitlement engine can analyze the usage history data to identify a subscription margin for the subscribed resources, reflecting collective under-consumption of resources by the set of users on a collective basis, over different and/or dynamically updated subscription periods. In aspects, the set of estimated resource contributions of different users can be aggregated over one or more dynamic resource contribution intervals to generated a bundled brokerage resource tender, in which the processor, operating system, and/or other resources of multiple users are combined to be offered to a cloud marketplace for one or more contribution interval. The bundled resource offer can be structured to contain at least a threshold amount of resources over a minimum or other defined contribution interval, after which resources are released back to the contributing users.

Dynamic reprovisioning of resources to software offerings

The disclosed embodiments provide a system that facilitates the maintenance and execution of a software offering. During operation, the system obtains a policy change associated with a service definition of the software offering. Next, the system updates one or more requirements associated with the software offering based on the policy change. Finally, the system uses the updated requirements to dynamically reprovision one or more resources for use by the software offering during execution of the software offering.

Mobile device workload management for cloud computing using sip and presence to control workload and method thereof

A method is implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions. The programming instructions are operable to manage workload for cloud computing by transferring workload to at least one mobile device using Session Initiation Protocol (SIP).

Information Handling System Application Decentralized Workload Management

A cloud application management infrastructure models biological swarm behaviors to assign application resources to physical processing resources in a decentralized manner. A balanced and highly automated management of cloud infrastructure has a predictable and reliable response to changing resource loads by using a limited local rule set to define how application instances interact with available resources. Digital pheromone signals at physical resources are applied locally by a swarm module to determine if the physical resources provide an acceptable environment for an application and, if not, the application swarms to other environments until a suitable environment is found.

System and method for managing a computing cluster

A method and system for managing a computing cluster including hosting a plurality of machines in a networked computing cluster, wherein the plurality of machines include service instances running on hosts, where the services have configured machine state; and wherein machine state includes configuration data and software of the machine; integrating the plurality of machines of the cluster with at least one configuration controller component; and the at least one configuration controller component, altering the machine state of at least one service instance.

Combining profiles based on priorities

Combining profiles based on priorities associated therewith to create an effective profile are provided. A plurality of profiles defining one or more rules that are applicable to a functional computing object are identified. A priority corresponding to each applicable profile is determined. The applicable profiles are combined by the computing device based on the corresponding priorities to create an effective profile that includes no conflicting rules.

Host Visibility as a Network Service

At a data switching device in a data center, it is detected whether a host has connected to a cloud computing network of which the data switching device and the data center are components. The detection is performed without directly communicating with the host. The data switching device determines properties of the host and generates a message comprising data representative of the properties of the host. The message is sent from the data switching device to a node in the cloud computing network that is configured to manage components of the cloud computing network associated with the host.

Managing Computer Resources in a Distributed Computing System

Methods, apparatus, and products for managing computer resources in a distributed computing system are disclosed that include registering, in a configuration management database by a discovery module in response to a modification of a resource in a resource container, the resource in association with a configuration management database identifier, the resource characterized by a resource type and a resource identification, the resource container including a manageability endpoint characterized by a manageability endpoint reference; and managing the resource by a management module in dependence upon a resource management policy and the manageability endpoint reference, the resource management policy including management actions for the resource.

Extensible support system for service offerings

Techniques are disclosed for integration, provisioning and management of entities and processes in a computing system such as, by way of example only, business entities and business processes. In particular, techniques are disclosed for implementing an extensible support system for multiple service offerings. For example, such a support system can be a business support system which may be employed in conjunction with a cloud computing environment.

Application Resource Manager over a Cloud

An application resource manager obtains a projection of upcoming demand for an application that runs on a cloud. The cloud includes at least one of an infrastructure as a service cloud and a platform as a service cloud. The application resource manager determines, based on the projection, that resources of the cloud that are devoted to the application need to be one of extended and shrunken. One of extending and shrinking the resources of the cloud that are devoted to the application is carried out in response to the determining.

Virtual computer and service

A virtual computer service includes receiving, at a network server computer over a network, an encrypted image and user credentials for a user of a computer, and storing the encrypted image and the user credentials in an image repository that is communicatively coupled to the network server computer. The virtual computer service also includes receiving a request to initiate a session, the request including the user credentials. Upon successful validation of the user credentials, the virtual computer service includes selecting the encrypted image from the image repository, decrypting the encrypted image, activating a session for a virtual computer associated with the computer, and synchronizing session details of the session, once completed, with the image and storing a synchronized image in the image repository.

Automated provisioning and management of cloud services

A system for managing the provisioning of cloud based services includes a collection module, a configuration module, a licensing module and a set up module. The collection module automatically obtains and stores information from end user machines that relevant to the provisioning of the could-based services. The configuration module uses the obtained information to automatically configure the use of the cloud based services. The licensing module automatically configures the account and licensing information allowing an end-user machine to access the cloud based services. The setup module automatically configures the end user machines to access and use the cloud-based services.

Thin client system, and access control method and access control program for thin client system

To heighten security in a thin client system, the thin client system includes: a communication unit 21 that receives a user ID and terminal information including at least current position information from a client terminal 10 ; a policy information extraction unit 22 that extracts policy information relating to a security policy stored in association with the terminal information received by the communication unit 21 on the basis of the terminal information; a virtual machine allocation unit 32 that allocates a virtual machine virtualizing an environment of the client terminal 10 to a server device 30 on the basis of the user ID received from the client terminal 10 ; and an access control unit 33 that restricts access to the virtual machine allocated by the virtual machine allocation unit 32 on the basis of the policy information extracted by the policy information extraction unit 22.

System and Method for Customer Provisioning in a Utility Computing Platform

Systems and methods are provided for provisioning a virtual server. An identification of an operating system, a server name, a number of processors, a memory amount, and a disk storage amount may be received, and a virtual server may be provisioned by provisioning a number of processors, an amount of memory, and an amount of storage resources based on the identified number of processors, the identified memory amount, and the identified disk storage amount. Resource usage of the virtual server may be monitored, and additional resources for the virtual server may be provisioned if burst resource usage mode is enabled for the virtual server.

Systems and methods of host-aware resource management involving cluster-based resource pools

Systems and methods are disclosed for managing resources associated with cluster-based resource pool(s). According to illustrative implementations, innovations herein may include or involve one or more of best fit algorithms, infrastructure based service provision, tolerance and/or ghost processing features, dynamic management service having monitoring and/or decision process features, as well as virtual machine and resource distribution features.

Method and device for agile computing

A method for operating a group of nodes in a system for agile computing comprising a coordinator node and a first computation node communicating via a connection, and wherein the first computation node is adapted to perform a task for the coordinator node is provided. The method comprises the steps of: monitoring at least one operating parameter indicating the quality of the connection between the two nodes; determining a quality parameter based on the operating parameter, wherein the quality parameter indicates the quality of the connection between the two nodes; and transferring information from the first computation node to the coordinator node, when the value of the quality parameter falls within a transfer interval, wherein the information comprises information about a part of a task performed by the first computation node.

Cluster computing using special purpose microprocessors

In some embodiments, a computer cluster system comprises a plurality of nodes and a software package comprising a user interface and a kernel for interpreting program code instructions. In certain embodiments, a cluster node module is configured to communicate with the kernel and other cluster node modules. The cluster node module can accept instructions from the user interface and can interpret at least some of the instructions such that several cluster node modules in communication with one another and with a kernel can act as a computer cluster.

Systems and methods for providing hierarchy of support services via desktop and centralized service

The present solution provides increases in automation, scalability and efficiency for delivering technical support services to devices. Systems and methods of the present solution provide a hierarchy or layers of automated desktop services with remote technical support services, which may be automated. The present solution provides an on desktop automation support system that detects and automatically remediates problems on a device of the user. If the problem is not fixed or fixable via local automated remediation at the desktop, a centralized service may remotely deliver technical support services to the device in the form of automated support services delivered to the device or remote technical agents connecting remotely with the device. With the combination of local support automation, remote support automation, remote and onsite technicians, the centralized service may deliver a hierarchy or multi-layers of services to any device.

Managing Capacity in a Data Center by Suspending Tenants

A tenant comprising one or more users receives services from a cloud computing system (“CCS”). The CCS determines when a tenant is not using any services, and if so, the CCS initiates a tenant suspension process. The tenant suspension process involves suspending various asynchronous computing processes for the tenant, which execute otherwise execute even if no users of the tenant are currently accessing the CCS. After a period of non-use of the CCS, the tenant is suspended. The tenant is returned to an active state automatically when a user of the tenant logs-on to receive services.

Uniform Definition, Provision, and Access of Software Services on the Cloud

A method for accessing cloud computing services provided by service providers includes uniformly defining, provisioning, and accessing cloud computing services of multiple genres such as single-tenant, multi-tenant and third party cloud services. The method defines cloud services across genres in a standard manner, acquires cloud services across genres, and provides a unified access and view of all cloud services subscribed by a user. The cloud services are acquired across genres by identifying a provisioning mechanism based on the cloud service genre requested by the user, automatically activating necessary task flow for the identified mechanism, and enabling the user to access the requested service by providing access with a unified Identity and Access Management System.

Performance interference model for managing consolidated workloads in qos-aware clouds

The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform off-line modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads. The WPPI system uses an online consolidation algorithm, the offline models, and online monitoring to determine virtual machine to physical host assignments responsive to real-time conditions to meet cloud provider and/or cloud consumer goals.

Suggesting migration to a cloud computing infrastructure

Embodiments of the present invention relate to an approach for suggesting/recommending migration of an IT environment to a cloud computing infrastructure. Specifically, in a typical embodiment, historical incident data of an information technology (IT) environment is analyzed. Based on the historical incident data, it may be determined whether a problem is recurring in the IT environment. If so, it may then be determined whether the problem can be mitigated in the cloud computing infrastructure. For example, it may be determined whether the cost of mitigating the problem by migrating to the cloud computing infrastructure is less than the cost of loss due to the problem within the current IT environment. A report particular to the IT environment that identifies a benefit of migrating the IT environment to the cloud computing infrastructure may be generated.

Dynamically optimized distribuited cloud computing-based business process management (bpm) system

A workflow server can receive requests, each for a business process workflow conforming to a business process model. Each business process workflow can include a set of interdependent tasks. The workflow server can satisfy received requests by assigning tasks to different service providers that provide software services. Each of the tasks can be assigned to corresponding ones of the software services. For each task, the workflow server can also defines an allocated cost per software service, and a time allocation per software service for completing the corresponding one of the tasks. Different service providers, including those assigned to tasks, can receive information for ones of the tasks not directly assigned to them by the workflow server. The different service providers can then bid on these tasks. Wherein when bids are won, tasks for a business process flow can be reassigned based on winning bids.

Method for fulfillment of kit and apparatus associated therewith

A method for fulfillment of a kit includes a) generating a 3D virtual simulation of a kit using a computer animation tool in a kit fulfillment environment after receiving a kit request from a customer, the 3D virtual simulation formed using 3D virtual models of objects in the kit and reflecting a spatial layout of components packed in a receptacle, the 3D virtual simulation including an interactive animation that dynamically controls a visual rendering of the 3D virtual simulation in response to a user at a user device selectively manipulating the kit or an object; b) providing the customer with remote access to the 3D virtual simulation to use a remote user device to control the visual rendering for a review of the kit; and c) releasing the kit for production and fulfillment of the request after receiving an approval from the customer in conjunction with the review.

Managing risk in resource over-committed systems

Risk associated with over-committing shared resources is determined. In response to receiving a request to provision a new workload, a candidate mix of virtual machines is selected from plurality of virtual machines already running on a cloud infrastructure. A utilization profile is then created for an aggregate behavior of the candidate mix of virtual machines and a new virtual machine running the new workload. A risk inherent in over-commitment if the new workload is grouped with the candidate mix of virtual machines is determined, and whether that risk is acceptable. If the risk is acceptable, the new workload is provisioned by over-committing the candidate mix of virtual machines with the new virtual machine running on the cloud infrastructure.

Monitoring geographic location changes of assets in a cloud

A monitoring tool can monitor network location of a digital asset hosted by a cloud service provider. Movement of the digital asset from a first network location to a second network location is detected. In response to detecting that the digital asset moves, a geographic location that corresponds to the second network location is determined. It is then determined that the geographic location deviates from a geographic setting configured for the digital asset. A notification that the digital asset has been moved to the geographic location that deviates from the geographic setting is generated.

Methods and Apparatus to Allocate Resources Associated with a Distributive Computing Network

Methods and apparatus to allocate resources associated with a distributive computing network are disclosed. A disclosed example method includes receiving resource allocation information associated with a service that is to be hosted by a distributive computing network, determining a first configuration type and a second configuration type specified within the received resource allocation information, determining at least one configuration group associated with the first configuration type and at least one configuration group associated with the second configuration type, determining physical resources included within the distributive computing network to host the service, electronically allocating the physical resources for the at least one configuration group associated with the first configuration type, electronically allocating the physical resources for the at least one configuration group associated with the second configuration type, and hosting the service within the physical resources in accordance with the allocations.

Automation of data storage activities

A system allows user to design data storage system workflows by selecting on a user interface various data objects associated with data storage system related activities. The activities include computer-executable instructions and can be predefined or determined by the user. Once the workflow is created, the workflow is deployed to one or more workflow engines that can execute the various data storage activities related to the workflow. Prior to executing a data storage activity, the system can determine which workflow engine to use based on an allocation scheme.

Electronic device, cloud storage system for managing cloud storage spaces, method and tangible embodied computer readable medium thereof

The present invention discloses an electronic device, a cloud storage system, a method thereof and a tangible embodied computer readable medium. The cloud storage system comprises at least one server and an electronic device. The at least one server provides a plurality of cloud storage spaces for accessing data. The electronic device comprises a storage management interface and is connected to each of the servers via Internet in order to access the cloud storage space. Wherein, the cloud storage spaces are integrated as a virtual storage space by the electronic device for a user to access data therefrom. The user can concurrently access the cloud storage spaces through the storage management interface of the electronic device, or access one of the cloud storage spaces by multi-thread or multi-process so as to raise the access speed.

Virtual Block Devices

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for virtual block storage. In one aspect, a method includes receiving a request to initialize a virtual machine, the virtual machine having an associated virtual block device; accessing a file map comprising a plurality of file map entries; determining file map entries corresponding to blocks of data allocated to the virtual block device and one or more files in which the blocks of data allocated to the virtual block device are stored; determining that a particular one of the blocks allocated to the virtual block device has been written to a new position not associated with the particular block in the file map; and updating the position associated with the particular block to the new position.

System and method for migrating application virtual machines in a network environment

A method includes managing a virtual machine (VM) in a cloud extension, where the VM is part of a distributed virtual switch (DVS) of an enterprise network, abstracting an interface that is transparent to a cloud infrastructure of the cloud extension, and intercepting network traffic from the VM, where the VM can communicate securely with the enterprise network. The cloud extension comprises a nested VM container (NVC) that includes an emulator configured to enable abstracting the interface, and dual transmission control protocol/Internet Protocol stacks for supporting a first routing domain for communication with the cloud extension, and a second routing domain for communication with the enterprise network. The NVC may be agnostic with respect to operating systems running on the VM. The method further includes migrating the VM from the enterprise network to the cloud extension through suitable methods.

Method of managing computing tasks in a wind farm

A method of managing computing tasks in a wind farm is provided. The method comprises determining the status of a plurality of wind turbines in the wind farm, determining available computing resources based on the status of the plurality of wind turbines, and allocating a portion of the computing tasks to the available computing resources for processing.

Reservation of resources and deployment of applications using an integrated development environment

Systems and methods to reserve resources is provided. In exemplary embodiments, a selection of a profile from a user is received. A dynamic graphical user interface is generated, using one or more processors. The dynamic graphical user interface allows the user to configure a topology based on the selected profile. The dynamic graphical user interface provides input fields in which the user may select a resource. An indication of the selected applicable topology property for configuring the topology is received. A topology is automatically generating based in part on the selected applicable topology property.

System and Method for a Self-Optimizing Reservation in Time of Compute Resources

A system and method of dynamically controlling a reservation of resources within a cluster environment to maximize a response time are disclosed. The method embodiment of the invention comprises receiving from a requestor a request for a reservation of resources in the cluster environment, reserving a first group of resources, evaluating resources within the cluster environment to determine if the response time can be improved and if the response time can be improved, then canceling the reservation for the first group of resources and reserving a second group of resources to process the request at the improved response time. 1. A method comprising:receiving from a requestor, at a first time, a request for a reservation of resources in a compute environment, the request comprising at least one of a required criteria and a preferred criteria;establishing the reservation such that a second time is set for workload to use a first group of resources;evaluating, prior to the second time, resources within the compute environment to determine if the second time should be modified to determine if the preferred criteria can be met by migrating the advance reservation in time, to yield an evaluation;if the evaluation indicates that the second time for the advance reservation should be modified, comparing the reservation and the first group of resources with a result of migrating the reservation from the first group of resources at the second time to a second group of resources at a third time, to yield a comparison; andif the comparison indicates the result of migrating the reservation yields a benefit relative to using the reservation of the first group of resources, then migrating, prior to the second time, the reservation from the first group of resources at the second time to the second group of resources at the third time.2. The method of claim 1 , wherein the second time claim 1 , when established claim 1 , is considered a fixed time for the reservation.3. The method of ...

Cloud system and method for connecting virtual machines in the cloud system

A method for connecting virtual machines in a cloud system is disclosed, wherein an agent network management service (Network management service, ANMS) process is used for communicating with all switches in the cloud system. When a virtual machine (VM) is created on one of the physical host in the cloud system, the ANMS detects the creation of the new VM, and confirms the virtual local area network (VLAN) the new VM pertained to. Next, determine a nearest boundary point from the new VM in the same VLAN for confirming a shortest connecting route. Lastly, the ANMS informing all switches in the shortest connecting route to set up internal VLAN tags such that new VM establish connection with other VMs in the same VLAN via the shortest connecting route.

Locally backed cloud-based storage

A popular service offered by many cloud computing systems is cloud-based storage. To enhance this service, the cloud-based storage can be extended through the use of a local storage device. A local storage device, such as a network enabled external hard drive, can be made available via a user's Internet connection. The local storage device can then be used to transparently store the user's content. That is, the user can still back up their devices to the cloud, but in some cases instead of the content residing in the cloud-based storage, it can reside on the local storage device without additional action required by the user. When the user requests the content, the content can be retrieved from the local storage device and returned to the requesting client device without the client device knowing where the content was stored.

Heterogeneous Parallel Primitives Programming Model

With the success of programming models such as OpenCL and CUDA, heterogeneous computing platforms are becoming mainstream. However, these heterogeneous systems are low-level, not composable, and their behavior is often implementation defined even for standardized programming models. In contrast, the method and system embodiments for the heterogeneous parallel primitives (HPP) programming model disclosed herein provide a flexible and composable programming platform that guarantees behavior even in the case of developing high-performance code.

Distributed fabric architecture in a cloud computing environment

A device creates a local forwarding function in a virtual machine of a device associated with a cloud computing environment, where the local forwarding function local forwarding function connects the device with local devices associated with the cloud computing environment. The device creates a global forwarding function in the virtual machine, where the global forwarding function connects the device with global devices associated with other cloud computing environments. The device also creates, in the virtual machine, a virtual control plane that controls the local forwarding function and the global forwarding function. The device communicates, via the local forwarding function, first traffic with a particular local device of the local devices, and communicates, via the global forwarding function, second traffic with a particular global device of the global devices.

Clientless Cloud Computing

Methods, apparatuses and articles of manufacture for clientless cloud-computing are provided. Clientless cloud-computing may be implemented by detecting a plurality of input/output devices, at least a portion of the plurality of input/output devices associated with a unique identifier and available to be communicatively bound to a cloud-resident computer. A binding preference, including a selection of an input/output device, is received. The selection includes the unique identifier associated with the selected input/output device. A binding request to the selected input/output device is transmitted, and the selected input/output device is communicatively bound with the cloud-resident computer.

System and Method for Enforcing Future Policies in a Compute Environment

A disclosed system receives a request for resources, generates a credential map for each credential associated with the request, the credential map including a first type of resource mapping and a second type of resource mapping. The system generates a resource availability map, generates a first composite intersecting map that intersects the resource availability map with a first type of resource mapping of all the generated credential maps and generates a second composite intersecting map that intersects the resource availability map and a second type of resource mapping of all the generated credential maps. With the first and second composite intersecting maps, the system can allocate resources within the compute environment for the request based on at least one of the first composite intersecting map and the second composite intersecting map. 1. A method comprising:establishing a standing reservation via a workload manager for compute resources within a compute environment, wherein the standing reservation is periodic and comprises a first reservation of a group of compute resources at a first time to yield a first group of reserved compute resources and a second reservation of the group of compute resources at a second time to yield a second group of reserved compute resources;receiving a request for compute resources to process a job from a user;receiving, with the request, an optimization request for the job;modifying one of the first group of reserved compute resources and the second group of reserved compute resources according to the optimization request to yield a modified group of compute resources; andinserting the job into the modified group of compute resources for processing.2. The method of claim 1 , wherein the workload manager receives requests for the compute resources in the compute environment and makes reservations for the compute resources to accommodate the requests.3. The method of claim 1 , wherein the standing reservation is created and ...

Multi-tenant-cloud-aggregation and application-support system

The present application is directed to a distributed system that provides multi-cloud aggregation and that includes a cloud-connector server, cloud-connector nodes, and one or more service-provider nodes that cooperate to provide services that are distributed across multiple clouds. A service-provider node obtains tenant-associated information from a virtual data center in which the service-provider node is installed and provides the tenant-associated information to the cloud-connector server.

Networked system of intelligent lighting devices with sharing of processing resources of the devices with other entities

A system of network-connected lighting devices also offers a distributed processing function that utilizes processor and/or memory resources if/when available in some or all of the lighting devices. In the examples, a resource manager receives a job for distributed processing using shared available resources. The resource manager identifies lighting devices having resources of the processors and/or the memories available for the distributed processing function. The resource manager distributes tasks and/or data of the received job through a communications network to identified lighting devices, for distributed processing. The resource manager also receives results of distributed processing for the received job, from the identified lighting devices through the communications network. The received results are processed to produce a composite result for a response to the received job.

Systems and Methods for Providing Hot Spare Nodes

Systems and methods for providing hot spare nodes are disclosed. For example, one disclosed method for providing hot spare nodes comprises receiving an indication of a first quantity of unallocated nodes, the first quantity greater than or equal to one; receiving a command configured to create a hot spare pool and causing the first quantity of unallocated nodes to be configured as a first quantity of configured nodes; and generating the hot spare pool, the hot spare pool comprising the first quantity of configured nodes.

System and Method for Providing Dynamic Roll-Back Reservations in Time

A systems, method and computer-readable media are disclosed for providing a dynamic roll-back reservation mask in a compute environment. The method of managing compute resources within a compute environment includes, based on an agreement between a compute resource provider and a customer, creating a roll-back reservation mask for compute resources which slides ahead of current time by a period of time. Within the roll-back reservation mask, the method specifies a subset of consumers and compute resource requests which can access compute resources associated with the roll-back reservation mask and, based on received data, the method dynamically modifies at least one of (1) the period of time the roll-back reservation mask slides ahead of current time and (2) the compute resources associated with the roll-back reservation mask. 1. A method comprising:identifying compute resources within a compute environment to yield identified data;based on the identified data, creating a policy-enforcing mechanism that manages and constrains establishment of reservations of compute resources for use by jobs; andestablishing a reservation for compute resources within the compute environment, wherein the establishing of the reservation is either constrained by the policy-enforcing mechanism or not constrained by the policy enforcing mechanism based on whether a request matches a parameter.2. The method of claim 1 , wherein the parameter is a need type.3. The method of claim 1 , further comprising:creating a set of non-consumption reservation masks covering multiple nodes in the compute environment, wherein multiple reservations created from multiple consumer requests are each constrained to only use at least a portion of the multiple nodes covered by the set of non-consumption reservation masks.4. The method of claim 1 , wherein the policy-enforcing mechanism is a non-consumption reservation mask.5. The method of claim 1 , wherein creating the policy-enforcing mechanism further ...

System and method for orchestration of services for use with a cloud computing environment

A system and method for orchestration of services for use with a cloud computing environment. In accordance with an embodiment, a cloud platform enables provisioning of enterprise software applications within a cloud environment, including packaging enterprise applications as service definition packages (SDP), and instantiating the services using service management engines (SME). In an embodiment, an orchestration engine communicates with a plurality of SMEs to control the flow of service creation, provider dependency resolution, association of services and providers, and the life-cycle management of services within the cloud platform.

System and method for providing a service management engine for use with a cloud computing environment

A system and method for providing a service management engine for use with a cloud computing environment. In accordance with an embodiment, enterprise software applications (e.g., Fusion Middleware applications) can be instantiated as services within a cloud platform, where they are then made accessible by other (e.g., customer) applications. In an embodiment, a service management engine (SME), in communication with an orchestration engine, can be used to provision services as one or more different service types, according to a service definition package (SDP). Service types can be instantiated according to the configuration of the cloud platform itself, and the contents of the SDP, including discovering, provisioning, and associating service types with system resources, to address different customer requirements.

Service association model

Enabling associations between cloud services in a computer network cloud infrastructure system is described. Cloud services can include infrastructure as a service (IAAS) storage and processing services, platform as a service (PAAS) database and Java services, and software as a service (SAAS) customer resource management services. Associations between the services can include automatically sharing security certificate-based keys and tokens or otherwise sharing data. Upon subscribing to a cloud system through an automated system, a user is prompted to select allowable associations between the selected services. The services are then provisioned and the user-selected associations are enabled.

System and method for service definition packages for use with a cloud computing environment

A system and method for providing service definition packages for use with a cloud computing environment. In accordance with an embodiment, a cloud platform enables provisioning of enterprise software applications (e.g., Fusion Middleware applications) within a cloud environment. In an embodiment, enterprise applications can be packaged as service definition packages (SDP). Each SDP can include an application binary component, a metadata defining the application's service characteristics and requirements, and a plugin that enables the SDP to be installed into the cloud platform. The SDP can also include a virtual assembly that defines a topology and configuration for a set of virtual appliances. The application, as defined by its SDP, can be instantiated as one or more services that are then accessible by other (e.g., customer) applications within the cloud environment.

Service Process Integration Systems and Methods

In some embodiments, multiple heterogeneous information technology service management (ITSM) applications of different IT service partners (customers and service providers) are integrated via a service process integration grid employing a set of standard workflows and associated standard transaction types and data structures. Once a service partner's workflows and data structures have been mapped to the standard grid workflows and data structures, integration with a first and new service partners is relatively fast and convenient. Analysis of real-life ITSM applications led to the development of particular standardized workflows classified according to whether they are initiated by service provider or customer, and according to whether they do or do not include ownership-transfer transactions allowing a service partner (customer or provider) to transfer ownership of the service process to its counterpart for further action by the counterpart.

COMMAND-AWARE HARDWARE ARCHITECTURE

In an embodiment, responsive to determining: (a) a first command is not of a particular command type associated with one or more hardware modules associated with a particular routing node, or (b) at least one argument used for executing the first command is not available: transmitting the first command to another routing node in the hardware routing mesh. Upon receiving a second command of the command bundle and determining: (a) the second command is of the particular command type associated with the hardware module(s), and (b) arguments used by the second command are available: transmitting the second command to the hardware module(s) associated with the particular routing node for execution by the hardware module(s). Thereafter, the command bundle is modified based on execution of the second command by at least refraining from transmitting the second command of the command bundle to any other routing nodes in the hardware routing mesh. 1. A hardware routing mesh , comprising:a plurality of routing nodes associated respectively with a plurality of hardware modules, the plurality of routing nodes comprising a first routing node communicatively coupled to a first hardware module of the plurality of hardware modules, receiving a first command of a command bundle being streamed through the plurality of routing nodes, wherein the command bundle is modified based on execution of commands as the command bundle is streamed through the plurality of routing nodes;', 'responsive to determining that (a) the first command is not of a particular command type associated with the first hardware module, or (b) at least one argument used for executing the first command is not received in association with the first command: transmitting the first command to a second routing node;', 'receiving a second command of the command bundle being streamed through the plurality of routing nodes;', 'responsive to determining that (a) the second command is of the particular command type ...

TRANSACTION-ENABLED METHODS FOR PROVIDING PROVABLE ACCESS TO A DISTRIBUTED LEDGER WITH A TOKENIZED INSTRUCTION SET

Transaction-enabled methods for providing provable access to a distributed ledger with a tokenized instruction set for polymer production processes are described. A method may include accessing a distributed ledger comprising an instruction set for a polymer production process and tokenizing the instruction set. The method may further include interpreting an instruction set access request and providing a provable access to the instruction set. The method may further include providing commands to a production tool of the polymer production process and recording the transaction on the distributed ledger. 1. A method , comprising:accessing a distributed ledger comprising an instruction set, wherein the instruction set comprises an instruction set for a polymer production process;tokenizing the instruction set;interpreting an instruction set access request;in response to the instruction set access request, providing a provable access to the instruction set;providing commands to a production tool of the polymer production process in response to the instruction set access request; andrecording a transaction on the distributed ledger in response to the providing commands to the production tool.2. The method of claim 1 , wherein the instruction set comprises an instruction set for a chemical synthesis subprocess of the polymer production process.3. The method of claim 2 , further comprising providing commands to a production tool of the chemical synthesis subprocess of the polymer production process in response to the instruction set access request and recording a transaction on the distributed ledger in response to the providing commands to the production tool of the chemical synthesis subprocess of the polymer production process.4. The method of claim 1 , wherein the instruction set comprises a field programmable gate array (FPGA) instruction set.5. The method of claim 1 , wherein the instruction set further includes an application programming interface (API).6. The ...

JOB DISTRIBUTION WITHIN A GRID ENVIRONMENT

According to one aspect of the present disclosure, a technique for job distribution within a grid environment includes receiving jobs at a submission cluster for distribution of the jobs to at least one of a plurality of execution clusters where each execution cluster includes one or more execution hosts. Resource attributes are determined corresponding to each execution host of the execution clusters. For each execution cluster, execution hosts are grouped based on the resource attributes of the respective execution hosts. For each grouping of execution hosts, a mega-host is defined for the respective execution cluster where the mega-host for a respective execution cluster defines resource attributes based on the resource attributes of the respective grouped execution hosts. Resource requirements for the jobs are determined, and candidate mega-hosts are identified for the jobs based on the resource attributes of the respective mega-hosts and the resource requirements of the jobs. 1. A method for job distribution within a grid environment , comprising:receiving jobs at a submission cluster for distribution of the jobs to at least one of a plurality of execution clusters, each execution cluster comprising one or more execution hosts;determining resource attributes corresponding to each execution host of the execution clusters;grouping, for each execution cluster, execution hosts based on the resource attributes of the respective execution hosts;defining, for each grouping of execution hosts, a mega-host for the respective execution cluster, the mega-host for a respective execution cluster defining resource attributes based on the resource attributes of the respective grouped execution hosts;determining resource requirements for the jobs; andidentifying candidate mega-hosts for the jobs based on the resource attributes of the respective mega-hosts and the resource requirements of the jobs.2. The method of claim 1 , further comprising grouping the execution hosts for a ...

Method and defragmentation module for defragmenting resources

A method and a defragmentation module for defragmenting resources of a hardware system. The defragmentation module identifies a set of structures. Each structure of the set of structures partially hosts a respective set of host machines. Respective resources of each host machine of the respective set of host machines are allocated in at least two structures of the set of structures. The defragmentation module selects, from the respective resources of a host machine of the respective set of host machine, a remote resource of a first structure being different from a second structure partially hosting the host machine. A remote amount of the remote resource is less than an amount of available resources of the second structure. The defragmentation module assigns the remote amount of the available resources of the second structure to the host machine instead of the remote resource.

CONTAINER-BASED APPLICATIONS

Provided is a method, computer program product, and system for adjusting a container-based application. A processor may receive one or more function calls at a container-based application. The processor may process the one or more function calls using the container-based application. The processor may obtain performance data from the container-based application based on the processing of the one or more function calls. The processor may analyze the performance data against a performance measure limit. The processor may adjust an aspect of the container-based application based on the analysis of the performance data. The aspect may be one or more selected from the group consisting of a resource and a functionality of the contain-based application. 1. A computer-implemented method comprising:receiving one or more function calls at a container-based application;processing the one or more function calls using the container-based application;obtaining performance data from the container-based application based on the processing of the one or more function calls;analyzing the performance data against a performance measure limit; andadjusting an aspect of the container-based application based on the analysis of the performance data, wherein the aspect is one or more selected from the group consisting of a resource and a functionality of the contain-based application.2. The computer-implemented method of claim 1 , wherein analyzing the performance data against the performance measure limit comprises determining whether the performance measure limit has been reached.3. The computer-implemented method of claim 1 , wherein analyzing the performance data against the performance measure limit comprises determining whether the performance measure limit will be reached within a predetermined time period.4. The computer-implemented method of claim 1 , wherein analyzing the performance data comprises:determining a processing time for processing the one or more function calls; ...

METHOD AND A DEVICE COMPRISING AN EDGE CLOUD AGENT FOR PROVIDING A SERVICE

The embodiments herein relate to a device and a method performed by an edge cloud agent, the method comprising: receiving a request for resources; locating a computing device, in the network, capable in providing the requested resources; instantiating a secure container on the located computing device; setting up a VLAN/VPN connection to the secure container on the computing device; and allocating said resources to a storage instance based on available resources within the computing device. 1. A method performed by an edge cloud agent in an operator's network , the method comprising:receiving a request for resources;locating a computing device, in the network, capable of providing the requested resources;instantiating a secure container on the located computing device;setting up a Virtual Local Area Network/Virtual Private Network, VLAN/VPN, connection to the secure container on the computing device; andallocating said resources to a storage instance based on available resources within the computing device.2. The method according to claim 1 , wherein setting up a VLAN/VPN connection includes setting up a VLAN/VPN connection from a cloud termination point of the operator to the secure container on the computing device.3. The method according to claim 1 , further comprising:detecting a presence of at least one user device connected to the network where the computing device is residing and said user device is consuming said resources;when the user device leaves said network, informing said user device that the storage instance will be terminated within a predetermined time period; andterminating said storage instance upon expiry of the predetermined time period.4. The method according to claim 1 , further comprising:acquiring storage capabilities of the computing device; anddeploying or deleting at least one storage instance of the computing device on the basis of the acquired storage capabilities.5. The method according to claim 1 , further comprising:allowing ...

Cognitive cloud migration optimizer

Methods, computer program products, and systems are presented. The methods include, for instance: input data from the source environment, including application hosting data of each server in the source environment and one or more cloud type of the source environment. Candidate cloud types for target platform are listed and servers of the source environment are screened for eligibility for the migration. The target platform is selected by applying preconfigured selection rules on the application hosting data of each eligible server in the source environment. Migration recommendations for each eligible server in the source environment, including selected cloud type corresponding to the target platform, are produced.

AUTOMATION OF DATA STORAGE ACTIVITIES

A system receives data storage workflow activities that include computer-executable instructions for carrying out data storage workflow in a network data storage system. Once the workflow is received, the system deploys the workflow to one or more workflow engines that can execute the various data storage activities related to the workflow. Prior to executing a data storage activity, the system can determine which workflow engine to use based on an allocation scheme. 1. A method for allocating execution of a data storage workflow suite within a networked data storage system , the method comprising:causing a display to display a plurality of data storage display objects associated with a plurality of data storage activities;receiving relationship data associated with the plurality of data storage display objects, wherein the relationship data indicates an order in which data storage activities are to be performed for at least first and second client computing devices having one or more processors; 'one or more backup storage activities in which primary data generated by the first and second client computing devices and residing in primary storage is copied to and stored in secondary storage;', 'with a first computing system comprising one or more processors, generating a data storage workflow suite based at least in part on the received relationship data, the data storage workflow suite comprising executable instructions for carrying out the plurality of data storage activities, the plurality of data storage activities comprising'}deploying the data storage workflow suite to a workflow engine which executes on a second computing system comprising one or more processors;receiving an instruction to initiate the data storage workflow suite; identifying a first data agent for implementing at least one of the one or more backup storage activities, wherein the first data agent resides on the first client computing device and is configured to process first data in ...

Self-managed intelligent elastic cloud stack

A cloud resource control circuitry may provide an automatic, self-managed, and a real-time elasticity in an active cloud stack including a software stack. The cloud resource control circuitry particularly adjusts cloud computing resources allocated to the active cloud stack based on real-time remote monitoring of resource utilization of the software stack. The resource adjustment may be performed in a stepwise fashion, in a pipelined manner as to the various layers of a software stack, and using hierarchical approach as to levels of cloud computing resources (e.g., task/level, server level, virtual machine/cloud level), to provide a more efficient cloud computing environment.

OPPORTUNISTIC DATA ANALYTICS USING MEMORY BANDWIDTH IN DISAGGREGATED COMPUTING SYSTEMS

Respective memory devices are assigned to respective processor devices in a disaggregated computing system, the disaggregated computing system having at least a pool of the memory devices and a pool of the processor devices. An iterative learning algorithm is used to define data boundaries of a dataset for performing an analytic function on the dataset simultaneous to a primary compute task, unrelated to the analytic function, being performed on the dataset in the pool of memory devices using memory bandwidth not currently committed to the primary compute task, thereby efficiently employing the unused memory bandwidth to prevent underutilization of the pool of memory devices. 1. A method for optimizing memory bandwidth in a disaggregated computing system , by a processor device , comprising:assigning respective memory devices to respective processor devices in the disaggregated computing system, the disaggregated computing system having at least a pool of the memory devices and a pool of the processor devices; andusing an iterative learning algorithm to define data boundaries of a dataset for performing an analytic function on the dataset simultaneous to a primary compute task, unrelated to the analytic function, being performed on the dataset in the pool of memory devices using memory bandwidth not currently committed to the primary compute task such that the analytic function is performed on the dataset being resident in the pool of memory devices using unused memory bandwidth otherwise allocated to the primary compute task associated with the dataset resident in the pool of memory devices to extract information to aide in processing the data resident in the pool of memory devices, thereby efficiently employing the unused memory bandwidth to prevent underutilization of the pool of memory devices.2. The method of claim 1 , further including receiving user input for designating certain processor devices of the pool of processor devices to be used to perform ...

CLOUD ACCESS METHOD FOR IOT DEVICES, AND DEVICES PERFORMING THE SAME

A cloud access method of an internet of things (IoT) device and devices performing the cloud access method are disclosed. The cloud access method using a cloud proxy function includes receiving a first resource retrieval request of a client device from a cloud, extracting, from the first resource retrieval request, a device identification (ID) of a device including a resource for which a resource retrieval is requested, and transmitting a second resource retrieval request of the client device to the device based on the device ID. 1. A cloud access method using a cloud proxy function , comprising:receiving, from a cloud, a first resource retrieval request of a client device;extracting, from the first resource retrieval request, a device identification (ID) of a device comprising a resource for which a resource retrieval is requested; andtransmitting, to the device, a second resource retrieval request of the client device based on the device ID.2. The cloud access method of claim 1 , wherein:the first resource retrieval request comprises a proxy-uniform resource identifier (URI) option header, andthe proxy-URI option header is removed from the second resource retrieval request.3. The cloud access method of claim 2 , wherein the proxy-URI option header comprises the device ID.4. The cloud access method of claim 1 , wherein the device is a device that has not a cloud interworking function.5. The cloud access method of claim 1 , wherein the transmitting comprises:searching for the device ID and endpoint information of the device from a mapping list that is used for managing device-to-device (D2D) devices that have not a cloud interworking function for access to the cloud.6. The cloud access method of claim 1 , further comprising:requesting the cloud for registration of a cloud proxy device that supports the cloud proxy function; andreceiving an access token for the cloud proxy device that is issued by the requesting for the registration.7. The cloud access method of ...

High performance and grid computing with reliability quality of service control

High performance computing (HPC) and grid computing processing for seismic and reservoir simulation are performed without impacting or losing processing time in case of failures. A Data Distribution Service (DDS) standard is implemented in High Performance Computing (HPC) and grid computing platforms, to avoid the shortcomings of current Message Passing Interface (MPI) communication between computing modules, and provide quality of service (QoS) for such applications. QoS properties of the processing can be controlled.

Generic exposure of enterprise resource planning data using a cloud-based, on-demand service

The present disclosure describes methods, systems, and computer program products for providing generic exposure of enterprise resource planning (ERP) data using a cloud-based, on-demand service. One computer implemented method includes receiving a data request for backend data stored in a backend system apart from the cloud-based, gateway services environment, generating a request in the gateway services environment for a service to handle the received data request, transmitting the generated request to a service repository to retrieve an appropriate service definition based upon component data request parameters, instantiating an instance of a generic data provider based upon a returned service definition, retrieving a model of the returned service definition, the model describing a data structure of at least one data entity provided by the service defined by the service definition, and retrieving runtime data from the backend system using the retrieved model of the returned service definition.

Managing Capacity in a Data Center by Suspending Tenants

A tenant comprising one or more users receives services from a cloud computing system (“CCS”). The CCS determines when a tenant is not using any services, and if so, the CCS initiates a tenant suspension process. The tenant suspension process involves suspending various asynchronous computing processes for the tenant, which execute otherwise execute even if no users of the tenant are currently accessing the CCS. After a period of non-use of the CCS, the tenant is suspended. The tenant is returned to an active state automatically when a user of the tenant logs-on to receive services.

Task Execution By Idle Resources In Grid Computing System

Described herein, are methods and devices for execution of a task in a grid computing system. According to an implementation, free time-slots are identified and durations of the free time-slots are estimated, by an edge device, for execution of a sub-task. The free time-slots are indicative of an idle state of the edge device. At least one computation capability parameter of the edge device is determined by the edge device for execution of a sub-task during the free time-slots. An advertisement profile having at least one free time-slot, and the duration and the at least one computation capability parameter associated with the at least one free time-slot is created by the edge device. The advertisement profile is provided by the edge device to grid servers in the grid computing system for partitioning a main task to create a sub-task executable by the edge device. 1. A method for execution of a task in a grid computing system , the method comprising:identifying free time-slots and estimating durations of the free time-slots, by an edge device, for execution of a sub-task, wherein the free time-slots are indicative of an idle state of the edge device;determining, by the edge device, at least one computation capability parameter of the edge device for execution of a sub-task during the free time-slots;creating, by the edge device, an advertisement profile comprising at least one free time-slot, from amongst the free time-slots, and comprising the duration and the at least one computation capability parameter associated with the at least one free time-slot; andproviding, by the edge device, the advertisement profile to grid servers in the grid computing system for partitioning a main task to create a sub-task executable by the edge device.2. The method as claimed in claim 1 , wherein the at least one computation capability parameter comprises a computation speed claim 1 , an available memory claim 1 , and a network bandwidth during the free time-slots.3. The method as ...

HARDWARE PLACEMENT AND MAINTENANCE SCHEDULING IN HIGH AVAILABILITY SYSTEMS

A method of organizing computer resources includes receiving a specification defining a plurality of quiescence groups of independent component instances for each of at least two services, and performing a first load balancing of the quiescence groups across a plurality of physical servers to define a plurality of supergroups while assigning each of the physical servers across the supergroups. 1. A method of organizing resources of a computer system , the computer system being organized into a plurality of supergroups , each of the supergroups including at least one quiescence group of independent component instances executing on different physical servers comprising:determining a minimum achievable number of supergroups needed to perform a service of the computer system;sorting the quiescence groups in a plurality of services by resource consumption;sorting the supergroups by resource utilization; andselecting each of the quiescence groups sequentially beginning with a quiescence group having a heaviest resource consumption, and placing a currently selected quiescence group on a supergroup having a lowest resource utilization among the supergroups and into which the currently selected quiescence group fits, and within the supergroup having the lowest resource utilization placing the currently selected quiescence group on a physical service having a lowest resource utilization among the physical servers, and resorting the supergroups by resource utilization upon placing the currently selected quiescence group.2. The method of claim 1 , wherein placing the currently selected quiescence group on the supergroup having the lowest resource utilization among the supergroups and into which the currently selected quiescence group fits further comprises:determining that the currently selected quiescence group does not fit in any of the supergroups;adding a physical server to one of the supergroups having a highest resource utilization; andplacing the selected group on the ...

Cloud agnostic workload identity

Examples include a system and computer-implemented method to create a cloud native workload identity (CNWI) and assign the CNWI to an instance of a workload to be instantiated in a cloud computing environment of a cloud service provider (CSP); translate the CNWI into a cloud agnostic workload identity (CAWI) and assign the CAWI to the workload instance; and use the CAWI by the workload instance to communicate with other workloads in the same or a different CSP.

COMPUTERIZED METHODS AND SYSTEMS FOR MAINTAINING AND MODIFYING CLOUD COMPUTER SERVICES

Systems, methods, and other embodiments associated with modifying a computer-implemented service are described. In one embodiment, a method includes constructing pre-provisioned instances of a service within a first pool and constructing pre-orchestrated instances of the service within a second pool. In response to receiving a request to modify the service, a POM instance of the service is created with a modified version of executable code and assigned to a third pool. The pre-orchestrated instances within the second pool are then replaced using the POM instances from the third pool. 1. A non-transitory computer-readable medium storing computer-executable instructions that when executed by a processor of a computing device causes the processor to:construct pre-provisioned instances of a service within a first pool of a zone of computing resources, wherein the service executes executable code using the computing resources, and wherein a pre-provisioned instance comprises a computing environment of computing resources configured for subsequent installation and execution of the executable code of the service;construct pre-orchestrated instances of the service within a second pool of the zone, wherein a pre-orchestrated instance comprises a pre-provisioned instance within which the executable code of the service is installed in a non-executing state; and (i) create pre-orchestrated maintenance (POM) instances of the service by applying a modified version of the executable code for the service to one or more pre-provisioned instances from the first pool;', '(ii) assign the POM instances to a third pool and remove the one or more pre-provisioned instances from the first pool; and', '(iii) replace the pre-orchestrated instances within the second pool using the POM instances from the third pool making the POM instances available for provisioning., 'in response to receiving a request to modify the service2. The non-transitory computer-readable medium of claim 1 , wherein the ...

INTEGRATED INTELLIGENT BUILDING MANAGEMENT SYSTEM AND MANAGEMENT METHOD THEREOF

An integrated intelligent building management system and a management method thereof are disclosed. The system includes a first cloud management system having a project management database, an intelligent building system managed by the first cloud management system, and a second cloud management system connecting with the first cloud-management system through a transforming interface. The management method includes the following steps. The first cloud management system receives the corresponding data of the building controlled by the intelligent building system and stores that in the project management database. The second cloud management system is authorized to connect and access the project management database. An access action from the second cloud management system to the project management database is accepted. A format transformation to data corresponding to the access action is performed. The second cloud management system stores the transformed data to a demand database therein. 1. An integrated intelligent building management system , comprising:a first cloud management system, comprising a first cloud configuration platform and a project management database comprising a first transforming interface and a data transforming service module;an intelligent building system, connected with and managed by the first cloud management system, and a corresponding data of a building controlled by the intelligent building system being stored in the project management database; anda second cloud management system, comprising a second cloud configuration platform and a demand database comprising a second transforming interface;wherein the first cloud management system is connected with the second transforming interface of the second cloud management system through the first transforming interface and authorizes the second cloud management system to connect and access the project management database,the first cloud management system performs a format transformation to ...

Systems and Methods For Allocating and Managing Resources in an Internet of Things Environment Using Location Based Focus of Attention

A system for managing clouds of edge devices as an Infrastructure as a Service clouds includes an application server, a location based situational awareness subsystem and a cloud management subsystem. The cloud management subsystem includes a first API through which the application server makes request to the location based situational awareness subsystem and a conductor that searches for the optimal deployment of cloud resources that meet a set of constraints. A second API for managing and deploying applications on a selected set of the plurality of network connected devices. The system also includes a compute node that can interact with the selected set of the plurality of network connected devices to launch and manage containers on the selected set of the plurality of network connected devices.

Tracking asynchronous event processing

A messaging system receives a registration from a first microservice for one or more event types to publish, and the registration includes an event report policy. The messaging system receives a first event, and the first event is described by the event report policy. The first event is monitored as it is processed by a second microservice. An event report describing the results of the monitoring is delivered to the first microservice.

VIRTUALIZING GRAPHICS PROCESSING IN A PROVIDER NETWORK

Methods, systems, and computer-readable media for virtualizing graphics processing in a provider network are disclosed. A virtual compute instance is provisioned from a provider network. The provider network comprises a plurality of computing devices configured to implement a plurality of virtual compute instances with multi-tenancy. A virtual GPU is attached to the virtual compute instance. The virtual GPU is implemented using a physical GPU, and the physical GPU is accessible to the virtual compute instance over a network. An application is executed using the virtual GPU on the virtual compute instance. Executing the application generates virtual GPU output that is provided to a client device. 120.-. (canceled)21. A system , comprising:a plurality of virtual compute instances, implemented using central processing unit (CPU) resources and memory resources of one or more physical compute instances of a provider network;a host comprising one or more physical graphics processing units (GPUs) that implement a plurality of virtual GPUs that are accessible to the virtual compute instances over a network, the one or more physical GPUs distinct from the one or more physical compute instances that implements the virtual compute instances; and 'attach each of the plurality of the virtual GPUs to respective virtual compute instances of the plurality of virtual compute instances;', 'one or more computing devices configured to implement an elastic graphics service configured to 'execute an application using a respective attached virtual GPU of the plurality of virtual GPUs.', 'wherein one or more of the virtual compute instances are configured to22. The system as recited in claim 21 ,wherein the provider network comprises another host comprising one or more other physical graphics processing units (GPUs) that implement another plurality of virtual GPUs;wherein the other plurality of virtual GPUs are organized into a plurality of virtual GPU classes, each class having distinct ...

Performance Interference Model for Managing Consolidated Workloads In Qos-Aware Clouds

The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads. The WPPI system uses an online consolidation algorithm, the offline models, and online monitoring to determine virtual machine to physical host assignments responsive to real-time conditions to meet cloud provider and/or cloud consumer goals.

Optimized multi-component co-allocation scheduling with advanced reservations for data transfers and distributed jobs

Disclosed are systems, methods, computer readable media, and compute environments for establishing a schedule for processing a job in a distributed compute environment. The method embodiment comprises converting a topology of a compute environment to a plurality of endpoint-to-endpoint paths, based on the plurality of endpoint-to-endpoint paths, mapping each replica resource of a plurality of resources to one or more endpoints where each respective resource is available, iteratively identifying schedule costs associated with a relationship between endpoints and resources, and committing a selected schedule cost from the identified schedule costs for processing a job in the compute environment.

DISTRIBUTED DATA SET ENCRYPTION AND DECRYPTION

An apparatus including a processor caused to: receive sizes and data block encryption data for multiple encrypted data blocks from multiple node devices, wherein data block encryption data is separately generated and used by each node device to encrypt a portion of a data set to generate one of the multiple encrypted data blocks; for each encrypted data block, generate a corresponding map entry within map data to include size and data block encryption data; and in response to receiving size and data block encryption data for all encrypted data blocks, encrypt a portion of the map data to generate an encrypted map base, wherein the portion of map data includes at least a subset of the multiple map entries, and transmit the encrypted map base to one or more storage devices to be stored within a data file along with the multiple encrypted data blocks. 1. An apparatus comprising a processor component and a storage to store instructions that , when executed by the processor component , cause the processor component to perform operations comprising:transmit, to multiple node devices, a command to encrypt a data set distributed among the multiple node devices for storage; the data set is to be stored as multiple encrypted data blocks within a data file maintained by one or more storage devices;', 'each node device of the multiple node devices is to provide at least one encrypted data block of the multiple encrypted data blocks to be stored;', 'the organization of the multiple encrypted data blocks within the data file is to be indicated in map data that is to comprise multiple map entries;', 'each map entry of the multiple map entries is to correspond to an encrypted data block of the multiple encrypted data blocks; and', 'at least a subset of the multiple node devices are to each encrypt a portion of the data of the data set to generate at least one of the multiple encrypted data blocks at least partially in parallel;, 'receive, from at least one node device of the ...

DISTRIBUTED DATA SET ENCRYPTION AND DECRYPTION

An apparatus may include a processor component caused to: generate map entries in map data descriptive of encrypted data blocks within a data file; use first map block encryption data to encrypt a first map extension of the map data; transmit the encrypted first map extension for storage within the data file; store the first map block encryption data within the second map extension; use second map block encryption data to encrypt a second map extension of the map data after storage of the first map block encryption data therein; transmit encrypted second map extension for storage within the data file; store the second map block encryption data within the map base; use third map block encryption data to encrypt a map base of the map data after storage of the second map block encryption data therein; and transmit the encrypted map base for storage within the data file. 1. An apparatus comprising a processor component and a storage to store instructions that , when executed by the processor component , cause the processor component to perform operations comprising: each map entry of the multiple map entries is to correspond to an encrypted data block of the multiple encrypted data blocks, and is to include an indication of a data block size of the corresponding encrypted data block; and', 'each map entry is to include data block encryption data that is separately generated and used to encrypt a portion of the data set to generate the corresponding encrypted data block;, 'generate, by the processor component, multiple map entries in map data that is descriptive of an arrangement of multiple encrypted data blocks of a data set within a data file to be maintained by one or more storage devices, wherein the multiple map extensions comprises at least a first map extension and a second map extension;', 'the first map extension comprises a first subset of the multiple map entries that corresponds to a first subset of the multiple encrypted data blocks, and the first map ...

DISTRIBUTED DATA SET ENCRYPTION AND DECRYPTION

An apparatus includes a processor component of a first node device caused to receive data block encryption data and an indication of size of an encrypted data block distributed to the first node device for decryption, and in response to the data set being of encrypted data: receive an indication of the quantity of sub-blocks within the encrypted data block, and a hashed identifier for each data sub-block; use the data block encryption data to decrypt the encrypted data block to regenerate data set portions from the data sub-blocks; analyze the hashed identifier of each data sub-block to determine whether all data set portions are distributed to the first node device for processing; and in response to a determination that at least one data set portion is to be distributed to a second node device for processing, transmit the at least one data set portion to the second node device. 1. An apparatus comprising a processor component of a first node device and a storage to store instructions that , when executed by the processor component , cause the processor component to perform operations comprising: the data set is stored within a data file as multiple encrypted data blocks; and', 'each encrypted data block is generated by encryption of at least one data set portion of the data set using corresponding data block encryption data separately generated for each encrypted data block;, 'receive, at the first node device of multiple node devices, an indication of a processing task to perform with a data set and metadata indicative of an organization of data within the data set, whereinreceive, at the first node device, data block encryption data and an indication of a size of an encrypted data block of the multiple encrypted data blocks that is distributed to the first node device for decryption;analyze the metadata to determine whether the data of the data set is partitioned data; [ each data sub-block of the encrypted data block corresponds to a data set portion of the data ...

DATA MANAGEMENT IN MULTI-CLOUD COMPUTING ENVIRONMENT

A data transfer request is received from an application program hosted at a first location in a computing environment for transferring a given data set to a second location in the computing environment. The data transfer request comprises information identifying one or more data types of the given data set and one or more preferences associated with the transfer of the given data set. The second location is notified of the data transfer request. The method causes deployment of one or more data-aware services to optimize the given data set prior to transfer to the second location, wherein optimizing the given data set is performed based on the one or more data types of the given data set and the one or more preferences associated with the transfer of the given data set. For example, the data-aware services at the first location may comprise data deduplication and/or data compression. 1. A method , comprising:receiving a data transfer request from an application program hosted at a first location in a computing environment for transferring a given data set to a second location in the computing environment, wherein the data transfer request comprises information identifying one or more data types of the given data set and one or more preferences associated with the transfer of the given data set;notifying the second location of the data transfer request; andcausing deployment of one or more data-aware services to optimize the given data set prior to transfer to the second location, wherein optimizing the given data set is performed based on the one or more data types of the given data set and the one or more preferences associated with the transfer of the given data set;wherein the receiving, notifying and deployment causing steps are performed via one or more processing devices.2. The method of claim 1 , wherein the one or more data-aware services to optimize the given data set prior to transfer to the second location comprise one or more of a data deduplication ...

FACILITATING CLOUD NATIVE EDGE COMPUTING VIA BEHAVIORAL INTELLIGENCE

Behavioral intelligence can be used with cloud native computing to enhance software deployment for various infrastructures by analyzing and deploying software functions according to the various infrastructures. Because different providers can have their own systems and controls for managing their infrastructures, it is costly to deploy software functions that are coupled together. However, if the software functions are disaggregated and translated according to the systems and controls relative to the various infrastructures, then the software functions can be failed and scaled independently of one another, thereby generating efficiencies. 1. A method , comprising:receiving, by network equipment comprising a processor, software function data representative of a software function of a software application;in response to receiving the software function data, translating, by the network equipment, the software function for usage for a service provider identity, resulting in a translated software function;deploying, by the network equipment, the translated software function to a first infrastructure device associated with the service provider identity, resulting in a first deployed translated software function;based on prediction data representative of a prediction associated with the first deployed translated software function, disaggregating, by the network equipment, the first deployed translated software function, resulting in a first translated software function and a second translated software function; deploying, by the network equipment, the first translated software function to the first infrastructure device, resulting in a second deployed translated software function, and', 'deploying the second translated software function to a second infrastructure device, different than the first infrastructure device, resulting in a third deployed translated software function;, 'in response to disaggregating the first deployed translated software function determining, by ...

ADAPTIVE LIMITED-DURATION EDGE RESOURCE MANAGEMENT

Systems and techniques for adaptive limited-duration edge resource management are described herein. Available capacity may be calculated for a resource for a node of the edge computing network based on workloads executing on the node. Available set-aside resources may be determined based on the available capacity. A service request may be received from an application executing on the edge computing node. A priority category may be determined for the service request. Set-aside resources from the available set-aside resources may be assigned to a workload associated with the service request based on the priority category. 1. A system for limited duration resource allocation in an edge computing network comprising:at least one processor; and calculate available capacity for resources of a node of the edge computing network based on workloads executing on the node;', 'determine available set-aside resources of the node based on the available capacity, wherein the available set-aside resources designate resources of the node to be assigned to a workload for a limited duration of time;', 'receive a service request from an application executing on the edge computing node;', 'determine a priority category for the service request; and', 'assign, for a limited duration of time, a set-aside resource from the available set-aside resources of the node to a workload associated with the service request based on the priority category., 'memory including instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to2. The system of claim 1 , wherein the priority category is best effort and the memory further comprising instructions that cause the at least one processor to perform operations to:assign a preemption delay to the set-aside resources assigned to the workload;receive a second service request with a higher priority category;reclaim the set-aside resources from the workload; andreassign the set-aside resources to a ...

EXECUTION OF CONTAINERIZED PROCESSES WITHIN CONSTRAINTS OF AVAILABLE HOST NODES

The technology disclosed herein enables optimized managing of cluster deployment on a plurality of host nodes. In a particular embodiment, a method includes defining parameters of a cluster for executing a process that will execute in a plurality of containers distributed across one or more of the plurality of host nodes. The method further provides adding a first container portion of the plurality of containers to a first host node portion of the plurality of host nodes. After adding the first container portion, the method includes determining that a remaining host node portion of the plurality of host nodes will not support more of the plurality of containers and adjusting the parameters of the cluster to allow the process to execute on the first host node portion. 1. A method for managing cluster deployment on a plurality of host nodes , the method comprising:defining parameters of a cluster for executing a process that will execute in a plurality of containers distributed across one or more of the plurality of host nodes;adding a first container portion of the plurality of containers to a first host node portion of the plurality of host nodes;after adding the first container portion, determining that a remaining host node portion of the plurality of host nodes will not support more of the plurality of containers; andadjusting the parameters of the cluster to allow the process to execute on the first host node portion.2. The method of claim 1 , further comprising:after adjusting the parameters of the cluster:determining that the remaining host node portion will support one or more additional containers of the plurality of containers;adding the one or more additional containers to the remaining host node portion; andadjusting the parameters of the cluster to allow the process to execute with the one or more additional containers.3. The method of claim 2 , further comprising:adjusting one or more other processes on the plurality of host nodes to make resources ...

Distributed Computing Mesh

Novel tools and techniques are provided for implementing a distributed computing mesh, and, more particularly, for implementing a distributed computing mesh using a hierarchical framework to distribute workload across multiple computing nodes. In various embodiments, a hierarchical distributed computing mesh might be implemented using a plurality of network nodes. A first control node may assign at least one first network node as at least one second control node. The second control node might receive a computing task from the first control node. The second control node might designate additional network nodes to process one or more portions of the computing task. The second control node may then divide the computing task and send the one or more portions of the computing task to the additional network nodes for processing. The second control node may receive one or more processed portions of the computing task from the additional network nodes. 1. A method , comprising:assigning, with a first control node, at least one first network node as at least one second control node;receiving, with the at least one second control node, a computing task from the first control node, wherein the computing task is a portion of a computational problem;determining, with the at least one second control node, an amount of computing power necessary to process the computing task;designating, with the at least one second control node, one or more additional network nodes to process one or more portions of the computing task, based at least in part on the determined amount of computing power;sending, with the at least one second control node, the one or more portions of the computing task to the one or more additional network nodes for processing; andreceiving, with the at least one second control node and from the one or more additional network nodes, one or more processed portions of the computing task.2. The method of claim 1 , further comprising:combining, with the at least one ...

Continuous testing, integration, and deployment management for edge computing

Various aspects of methods, systems, and use cases for testing, integration, and deployment of failure conditions in an edge computing environment is provided through use of perturbations. In an example, operations to implement controlled perturbations in an edge computing platform include: identifying at least one perturbation parameter available to be implemented with a hardware components of an edge computing system that provides a service using the hardware components; determining values, which disrupt operation of the service, to implement the perturbation parameter among the hardware components; deploying the perturbation parameters to the hardware components, during operation of the service to process a computing workload, to cause perturbation effects on the service; collecting telemetry values associated with the hardware components, produced during operation of the service that indicate the perturbation effects upon the operation of the service; and cause a computing operation to occur based on the collected telemetry values.

SEAMLESS MULTI-CLOUD SDWAN DISTASTER RECOVERY USING ORCHESTRATION PLANE

The present disclosure is directed to management of migration of SD-WAN solutions in a multi-cloud structure upon detection of a failover event. In one aspect, a method includes monitoring, using virtual bonds of a network orchestration component, clusters of virtual management components of multiple cloud networks, corresponding virtual management components of one of the multiple cloud networks implementing one or more services of a Software-Defined Wide Access Network (SD-WAN) solution; detecting, using the virtual bonds, a failover event at the one of the multiple cloud networks; and identifying, by the virtual bonds, a new destination cloud network to migrate the one or more services of the SD-WAN solution to, from a source cloud network at which the failover event is detected. 1. A method comprising:monitoring, using virtual bonds of a network orchestration component, clusters of virtual management components of multiple cloud networks, corresponding virtual management components of one of the multiple cloud networks implementing one or more services of a Software-Defined Wide Access Network (SD-WAN) solution;detecting, using the virtual bonds, a failover event at the one of the multiple cloud networks; andidentifying, by the virtual bonds, a new destination cloud network to migrate the one or more services of the SD-WAN solution to, from a source cloud network at which the failover event is detected.2. The method of claim 1 , wherein each of the virtual bonds has an established secure channel to each virtual management component in each of the clusters.3. The method of claim 2 , wherein monitoring the clusters comprises:determining a number of inactive virtual management components of each of the multiple cloud networks.4. The method of claim 3 , wherein detecting the failover event comprises:determining, by each of the virtual bonds and based on the number of inactive virtual management components in the one of the multiple cloud networks, an active status ...