Distributed Caching Control Strategy in Mobile Edge Computing: A Mean Field Game Approach
2022 19th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)(2022)
摘要
Mobile edge computing (MEC) is a novel computing paradigm that sinks the computing capacity of cloud servers into edge nodes to reduce network latency. By caching the popular content at small base station (SBS) can reduce the heavy backhaul load and the content retransmission in MEC. However, the dynamic and time-varying of the content requests may increase the network cost. In this paper, we study a distributed edge caching optimization problem in MEC scenario with the spatio-temporal requirements. The considered cache control is described as a stochastic differential game (SDG) in which each SBS defines a caching strategy to reduce the cost in terms of the service delay and backhaul link load. To reduce the computational complexity, the original problem can be transformed into a mean field game (MFG). We propose a caching iterative control algorithm that decouples the information interactions between the general SBS and others with the mean field distribution. In addition, we obtain the optimal caching strategy which achieves the existence and uniqueness of the mean field equilibrium (MFE). Simulation results demonstrate that our proposed algorithm can reduce more storage space and total cost compared to the Kim's approach.
更多查看译文
关键词
Mobile edge computing,distributed edge caching,mean-field game approach,spatio-temporal requirements,optimal control
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要