QoS-aware Dynamic Service Caching and Updating in Cost-efficient Multi-Access Edge Computing
Shuaibing Lu, Xin Jin, Jie Wu, Shuyang Zhou, Shen Wu, Jackson Yang, Ran Yan · 2024
In the context of mobile edge computing, achieving dynamic service caching and updating to guarantee the QoS of users and reduce system costs is a challenging problem. However, existing research still has certain deficiencies in considering the dynamic behavior of users and the limited storage resources of edge servers. To address this problem, this paper proposes three novel strategies for the different stages of service caching and updating to jointly optimize the delay and cost. At the initial service caching stage, we propose a caching strategy based on dynamic programming, taking into account the constraint of limited memory resources. Given the dynamic behavior of users, we formulate the joint optimization problem as a Markov Decision Process (MDP) and design a service extension strategy based on Q-learning at the service updating decision-making stage and a replacement strategy taking both the distribution of service replications and service access frequency into account at the service updating replacement stage to guarantee the QoS of users. We effectively tackle the challenges arising from the dynamic behavior of users and limited storage resources. Through extensive comparative experiments, our approach outperforms traditional strategies by significantly reducing user latency and system cost.