Edge Caching Resource Allocation in Fog Radio Access Networks: An Incentive Mechanism Based Approach

被引:0
|
作者
Ge, Hui [1 ,2 ,3 ]
Jiang, Yanxiang [1 ,2 ,3 ]
Bennis, Mehdi [4 ]
Zheng, Fu-Chun [1 ,5 ]
You, Xiaohu [1 ]
机构
[1] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Jiangsu, Peoples R China
[2] Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Shaanxi, Peoples R China
[3] Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Key Lab Wireless Sensor Network & Commun, 865 Changning Rd, Shanghai 200050, Peoples R China
[4] Univ Oulu, Ctr Wireless Commun, Oulu 90014, Finland
[5] Harbin Inst Technol, Sch Elect & Informat Engn, Shenzhen 518055, Peoples R China
基金
英国工程与自然科学研究理事会;
关键词
F-RANs; edge caching; resource allocation; incentive mechanism; Stackelberg game; WIRELESS; DESIGN;
D O I
10.1109/iccw.2019.8757018
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, an edge caching resource allocation problem in fog radio access networks (F-RANs) is investigated. To motivate content providers (CPs) to participate in this resource allocation procedure, we introduce an incentive mechanism. By treating fog access points (F-APs) as a specific type of edge caching resource, the cloud server sets non-uniform prices of F-APs and leases them to the CPs, while the CPs cache the most popular contents in the storage of F-APs and get rewarded by the raised content hit rate. We formulate the interaction between the cloud server and the CPs as a Stackelberg game and solve the corresponding optimization problems to achieve Nash equilibrium (NE). In particular, by exploiting the multiplier penalty function method, we transform the constrained optimization problem for the cloud server into an equivalent non-constrained optimization problem. Then, we propose an edge caching resource pricing algorithm to solve the non-constrained optimization problem by applying the simplex search method. We also theoretically prove the existence and uniqueness of the NE. Simulation results show the rapid convergence of the proposed algorithm and the superiority performance in improving content hit rate.
引用
收藏
页数:6
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