H. Ge, Y. Jiang, M. Bennis, F. Zheng and X. You, "Edge Caching Resource Allocation in Fog Radio Access Networks: An Incentive Mechanism Based Approach," 2019 IEEE International Conference on Communications Workshops (ICC Workshops), Shanghai, China, 2019, pp. 1-6, https://doi.org/10.1109/ICCW.2019.8757018
Edge caching resource allocation in fog radio access networks : an incentive mechanism based approach
|Author:||Ge, Hui1,2,3; Jiang, Yanxiang1,2,3; 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, 3.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020050424739
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-05-04
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.
IEEE/CIC International Conference on Communications in China - Workshops
|Pages:||1 - 6|
2019 IEEE International Conference on Communications Workshops, ICC Workshops 2019; Shanghai; China; 20-24 May 2019 : Proceedings
IEEE International Conference on Communications Workshops
|Type of Publication:||
A4 Article in conference proceedings
|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 61521061 and grant 61871122, the Natural Science Foundation of Jiangsu Province under grant BK20181264, 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, the National Basic Research Program of China (973 Program) under grant 2012CB316004, and the U.K. Engineering and Physical Sciences Research Council under grant EP/K040685/2.
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.