Cooperative caching in fog radio access networks: a graph‐based approach. Issue 20 (1st December 2019)

• Record Type: Journal Article
• Authors: Jiang, Yanxiang; Cui, Xiaoting; Bennis, Mehdi; Zheng, Fu‐Chun; Fan, Baotian; You, Xiaohu
• Is Part Of: IET communications. Volume 13:Issue 20(2019)
• Page Start: 3519
• Page End: 3528
• Publication Date: 2019-12-01
• Subjects: pattern clustering -- optimisation -- greedy algorithms -- cache storage -- graph theory -- set theory -- knapsack problems -- radio access networks; effective graph‐based approach -- node graph -- weighted graph -- incremental offloaded traffics -- corresponding complete subgraphs -- objective cluster sets -- max‐weight independent subset -- graph‐based content placement approach -- redundancy graph -- content placement subproblem -- clustering subproblem -- challenging optimisation problem -- knapsack problems -- caching optimisation problem -- fog radio access networks -- offloaded traffic -- caching decisions; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2019.0436
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In this study, cooperative caching is investigated in fog radio access networks. To maximise the offloaded traffic, a cooperative caching optimisation problem is formulated. By analysing the relationship between clustering and cooperation and utilising the solutions of the knapsack problems, the above challenging optimisation problem is transformed into a clustering subproblem and a content placement subproblem. To further reduce complexity, the authors propose an effective graph‐based approach to solve the two subproblems. In the graph‐based clustering approach, a node graph and a weighted graph are constructed. By setting the weights of the vertices of the weighted graph to be the incremental offloaded traffics of their corresponding complete subgraphs, the objective cluster sets can be readily obtained by using an effective greedy algorithm to search for the max‐weight independent subset. In the graph‐based content placement approach, a redundancy graph is constructed by removing the edges in the complete subgraphs of the node graph corresponding to the obtained cluster sets. Furthermore, they enhance the caching decisions to ensure each duplicate file is cached only once. Compared with traditional approximate solutions, their proposed graph‐based approach has lower complexity. Simulation results show remarkable improvements in terms of offloaded traffic by using the proposed approach.