In this paper, the edge caching optimization problem in fog radio access networks (F-RANs) is investigated. Taking into account time-variant user requests and ultra-dense deployment of fog access points (F-APs), we propose a distributed edge caching scheme to jointly minimize the request service delay and fronthaul traffic load. Considering the interactive relationship among F-APs, we model the optimization problem as a stochastic differential game (SDG) which captures the dynamics of F-AP states. To address both the intractability problem of the SDG and the caching capacity constraint, we propose to solve the optimization problem in a distributive manner. Firstly, a mean field game (MFG) is converted from the original SDG by exploiting the ultra-dense property of F-RANs, and the states of all F-APs are characterized by a mean field distribution. Then, an iterative algorithm is developed that enables each F-AP to obtain the mean field equilibrium and caching control without extra information exchange with other F-APs. Secondly, a fractional knapsack problem is formulated based on the mean field equilibrium, and a greedy algorithm is developed that enables each F-AP to obtain the final caching policy subject to the caching capacity constraint. Simulation results show that the proposed scheme outperforms the baselines.
Jiang Yanxiang, Hu Yabai, Bennis Mehdi, Zheng Fu-Chun, You Xiaohu
A1 Journal article – refereed
Place of publication:
Y. Jiang, Y. Hu, M. Bennis, F. Zheng and X. You, “A Mean Field Game-Based Distributed Edge Caching in Fog Radio Access Networks,” in IEEE Transactions on Communications, vol. 68, no. 3, pp. 1567-1580, March 2020.
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