Jointly caching and computation resource allocation for mobile edge networks. Issue 5 (1st September 2019)

• Record Type: Journal Article
• Authors: Tang, Qinqin; Xie, Renchao; Huang, Tao; Liu, Yunjie
• Is Part Of: IET networks. Volume 8:Issue 5(2019)
• Page Start: 329
• Page End: 338
• Publication Date: 2019-09-01
• Subjects: pricing -- transcoding -- resource allocation -- cache storage -- scheduling -- cellular radio -- game theory; MEC server -- BSs -- caching/computing space -- storage -- computational capacities -- mobile edge networks -- computation resource allocation -- mobile edge computing -- fifth generation networks -- computing resources -- mobile networks -- joint caching -- computing resource allocation mechanism; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/iet-net.2018.5111
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract : To cope with the explosion of video traffic, mobile edge computing (MEC) has been introduced as a promising technology in fifth generation networks to enable caching and computing resources to transcode video contents and cache them within the edge of mobile networks. In this study, a joint caching and computing resource allocation mechanism is proposed to effectively schedule the resources of the mobile edge networks. The authors formulate a Stackelberg game to analyse the allocation problem between the MEC server and multiple base stations (BSs). The MEC server aims to impose the prices to the BSs to maximise its revenue, while the BSs compete to determine the caching/computing space that they can occupy at the MEC server to improve the quality of experience of their service users. The competition between the BSs is formulated as a non‐cooperative subgame where each BS is designed to maximise the request rate that can be served by the MEC server. Then, the proposed games are proved to converge to a unique Stackelberg equilibria. Numerical simulations are presented to verify the proposed scheme. It is shown that the proposed schemes are effective in resource allocation for both storage and computational capacities in mobile edge networks.