Machine learning-based and adaptive optimization method of ap selection
Номер патента: LU102762B1
Опубликовано: 11-03-2022
Автор(ы): Haitao Zhao, Hongbo Zhu, HUI Zhang, Jianguo Yu, Jiaxin Li, Tangwei Zhang
Принадлежит: Univ Nanjing Posts & Telecommunications
Опубликовано: 11-03-2022
Автор(ы): Haitao Zhao, Hongbo Zhu, HUI Zhang, Jianguo Yu, Jiaxin Li, Tangwei Zhang
Принадлежит: Univ Nanjing Posts & Telecommunications
Реферат: The present invention discloses a machine learning-based and adaptive optimization method of AP selection. The method is applied to a process of setting up WiFi connections between mobile devices and APs and a process of adaptive network handovers in the Internet of Vehicles. The method includes: collecting connected device data in the current environment, creating a training data set and a feature set, and determining a threshold; determining whether a decision tree is a single-node tree based on the data set and the ID3 algorithm; if the decision tree is not a single-node tree, obtaining subsets by division to construct subnodes and generate the tree; and perform recursive invoking until a complete decision tree is generated, classifying APs into a fast set and a slow set, and selecting the fastest AP from the fast set to set up a connection. In the present invention, access points (APs) are selected based on a machine learning model to shorten the connection time and reduce the time cost for WiFi connection setting.
Machine learning-based approaches for service function chain selection
Номер патента: US12133095B2. Автор: Puneet Sharma,FARAZ Ahmed,Lianjie Cao. Владелец: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP. Дата публикации: 2024-10-29.