Invention Publication
- Patent Title: OPTIMIZING KEY ALLOCATION DURING ROAMING USING MACHINE LEARNING
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Application No.: US18410839Application Date: 2024-01-11
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Publication No.: US20240147314A1Publication Date: 2024-05-02
- Inventor: Gopal Gupta , Abhinesh Mishra , Isaac Theogaraj , Sachin Ganu , Bernd Bandemer , Jose Tellado
- Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
- Applicant Address: US TX Spring
- Assignee: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
- Current Assignee: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
- Current Assignee Address: US TX Spring
- Main IPC: H04W36/00
- IPC: H04W36/00 ; G06N20/00 ; H04L41/16 ; H04W12/041 ; H04W88/08

Abstract:
Systems and methods are provided for optimizing resource consumption by bringing intelligence to the key allocation process for fast roaming. Specifically, embodiments of the disclosed technology use machine learning to predict which AP a wireless client device will migrate to next. In some embodiments, machine learning may also be used to select a subset of top neighbors from a neighborhood list. Thus, instead of allocating keys for each of the APs on the neighborhood list, key allocation may be limited to the predicted next AP, and the subset of top neighbors. In some embodiments, a reinforcement learning model may be used to dynamically adjust the size of the subset in order to optimize resources while satisfying variable client demand.
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