Dynamic theoretic proactive caching placement game for energy saving in H‐CRAN. (25th February 2020)

• Record Type: Journal Article
• Authors: Mrad, Safa; Hamouda, Soumaya
• Is Part Of: International journal of communication systems. Volume 33:Number 8(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-02-25
• Subjects: 5G -- caching placement -- edge caching -- energy saving -- proactive game; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.4371
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: Edge caching is an effective feature of the next 5G network to guarantee the availability of the service content and a reduced time response for the user. However, the placement of the cache content remains an issue to fully take advantage of edge caching. In this paper, we address the proactive caching problem in Heterogeneous Cloud Radio Access Network (H‐CRAN) from a game theoretic point of view. The problem is formulated as a bargaining game where the remote radio heads (RRHs) dynamically negotiate and decide which content to cache in which RRH under energy saving and cache capacity constraints. The Pareto optimal equilibrium is proved for the cooperative game by the iterative Nash bargaining algorithm. We compare between cooperative and noncooperative proactive caching games and demonstrate how the selfishness of different players can affect the overall system performance. We also showed that our cooperative proactive caching game improves the energy consumption of 40% as compared with noncooperative game and of 68% to no‐game strategy. Moreover, the number of satisfied requests at the RRHs with the proposed cooperative proactive caching scheme is significantly increased. Abstract : Proactive caching placement issue in H‐CRAN is addressed and modeled as a bargaining game. The RRHs negotiate with each other which content to cache locally under storage size and total transmit power consumption constraints. After proving the existence and the uniqueness of the Nash bargaining solution (NBS) mathematically, we showed by simulations that at the steady state, both energy efficiency of the system and cache hit ratio are increased as compared with noncooperative and no game–based approaches.