A user‐centric cooperative edge caching scheme for minimizing delay in 5G content delivery networks. Issue 8 (1st July 2018)

• Record Type: Journal Article
• Authors: Tang, Shiyu; Alnoman, Ali; Anpalagan, Alagan; Woungang, Isaac
• Is Part Of: Transactions on emerging telecommunications technologies. Volume 29:Issue 8(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-07-01
• Subjects: Telecommunication -- Periodicals; 384.05
• DOI: 10.1002/ett.3461
• Languages: English
• ISSNs: 2161-5748

Abstract

Abstract: This paper investigates the problem of user‐centric cooperative edge caching in content delivery networks to leverage service provisioning at the network edge and to improve the quality of experience by minimizing the end‐to‐end delay. By taking advantage of the major characteristics in fifth‐generation networks, users can access contents not only from the nearest small base station (SBS) but also from other SBSs in the vicinity that have the requested precached contents. In the proposed scheme, a user‐centric delivery approach is considered in such a way that the base station can respond to the user request as long as it has enough resources. To this end, a caching algorithm is introduced whereby a group of SBSs cooperatively share storage and decide on the caching policy together aiming to cache as much contents as possible under the capacity constraint. Moreover, a modified matching theory is used for content delivery taking the bandwidth requirements into account. Simulation results show that the proposed scheme can achieve 99.5% local serve ratio when the SBS has a caching capacity of 40 % the overall file size, and 20 available communication channels for content distribution. Abstract : Edge caching is envisioned to play a vital role in 5G content delivery networks that is aimed to reduce service delay experienced by users. To this end, we investigate the problem of content caching by considering a cooperative edge caching scheme in which small base stations located in the vicinity of mobile users can share storage and cooperatively decide on the caching policy. The proposed scheme was successful in achieving 99.5% local hit ratio under limited storage capacity and bandwidth resources.