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.
A mean field game-based distributed edge caching in fog radio access networks
|Author:||Jiang, Yanxiang1,2,3; Hu, Yabai1; Bennis, Mehdi4;|
1National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
2State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, China
3Key Laboratory of Wireless Sensor Network & Communication, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 865 Changning Road, Shanghai 200050, China
4Centre for Wireless Communications, University of Oulu, Oulu 90014, Finland
5School of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen 518055, China
|Online Access:||PDF Full Text (PDF, 5.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202001303915
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-01-30
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.
IEEE transactions on communications
|Pages:||1567 - 1580|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by the Natural Science Foundation of China under Grant 61971129, the Natural Science Foundation of Jiangsu Province under Grant BK20181264, the National Key R&D Program of China under Grant 2018YFB1801103, the Research Fund of the State Key Laboratory of Integrated Services Networks (Xidian University) under Grant ISN19-10, the Research Fund of the Key Laboratory of Wireless Sensor Network & Communication (Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences) under Grant 2017002, and the Research Fund of the School of Electronic and Information Engineering, Harbin Institute of Technology (Shenzhen) under Grant HITSZ20190631.
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