Efficient caching strategy in wireless networks with mobile edge computing
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Efficient caching strategy in wireless networks with mobile edge computing Ying Chen1
· Shuang Chen1 · Xin Chen1
Received: 30 August 2019 / Accepted: 3 January 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract With the increasing popularity of Internet of things (IoT) applications, mobile edge computing (MEC) is emerging as a new technology. Caching popular content to edge servers can effectively reduce backhaul time and satisfy a large number of users’ access requests for the content. However, edge caching faces the problems of limited storage capacity in the edge server and limited service scope in MEC. Therefore, edge caching should consider allocating the limited caching resources reasonably to different content providers (CP) to obtain the high caching utility. In this paper, we study caching in a multiCP scenario with multiple users. In the process of defining content popularity, we consider that CPs overall popularity degree satisfies the law of diminishing marginal effect, and define the user satisfaction function as the benefit of caching. Then, aiming at maximizing caching utility, we establish a game model of caching resource competition among CPs based on noncooperative game, and prove the existence of Nash equilibrium (NE). In addition, the Best Response based MultiCP Caching (BRMC) algorithm is proposed to obtain the best caching strategy. Finally, iterative experiments validate the convergence of the BRMC, and comparative experiments show that the BRMC can achieve a high caching utility. Keywords Edge caching · Mobile edge computing · Noncooperative game · Nash equilibrium
1 Introduction With the advent of the era of 5G, the number of Internet of things (IoT) applications has increased greatly [1, 2]. The surge of network traffic leads to the increase of execution delay and large consumption of energy, resulting in poor quality of user experience (QoE) [3, 4]. Mobile edge computing (MEC) appears as an emerging technology. Different from the cloud computing, MEC provides computing and storage resources at the edge of the This article is part of the Topical Collection: Special Issue on Emerging Trends on Data Analytics at the Network Edge Guest Editors: Deyu Zhang, Geyong Min, and Mianxiong Dong Ying Chen
[email protected] Shuang Chen [email protected] Xin Chen [email protected] 1
School of Computer Science, Beijing Information Science and Technology University, Beijing, China
network, which alleviates the pressure of network traffic. User requests can be processed at the edge servers which are close to users, rather than being transported to the cloud. It can effectively shorten delay and reduce energy consumption [5–8]. Caching content to the edge server can also greatly reduce the time and energy consumption during content transmission and bring better QoE [9–11]. With the increasing popularity of social media, video traffic becomes the main part of network data [12]. Edge caching can reduce latency of network tasks with large data backhaul (e
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