Mobility-aware personalized handover function provisioning system in B5G networks

Current 5G networks suffer from high signaling overhead due to highly mobile vehicles. In this paper, we first introduce a personalized handover function (denoted μHF) that consolidates all handover-related functionalities for individual mobile devices (MDs). Recognizing that the location of μHF affects overall handover performance, we propose a mobility-aware μHF provisioning system (MA-μHFPS), which utilizes a central controller to collect mobility information for each MD and provisions μHFs in the edge cloud for MDs that are expected to have high mobility for a long time. To minimize signaling overhead and migration cost for handover-related information from the central cloud to the edge cloud while ensuring that the average required resource of the edge cloud remains below a specific threshold, we formulate a constrained Markov decision process (CMDP) problem. By converting the CMDP problem into a linear programming (LP) model, we can achieve an optimal stochastic policy using a traditional algorithm with low complexity. Evaluation results demonstrate that MA-μHFPS significantly reduces signaling overhead with a small state migration cost compared to the traditional handover management system.