ICN with edge for 5G: Exploiting in-network caching in ICN-based edge computing for 5G networks
- Authors
- Ullah, Rehmat; Rehman, Muhammad Atif Ur; Naeem, Muhammad Ali; Kim, Byung-Seo; Mastorakis, Spyridon
- Issue Date
- Oct-2020
- Publisher
- ELSEVIER
- Keywords
- 5G; Radio access network; Mobile edge caching; Information-centric networking; Device to device communication; Content popularity; Backhaul traffic reduction; Future networks
- Citation
- FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, v.111, pp.159 - 174
- Journal Title
- FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
- Volume
- 111
- Start Page
- 159
- End Page
- 174
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/11534
- DOI
- 10.1016/j.future.2020.04.033
- ISSN
- 0167-739X
- Abstract
- In recent years, edge computing and Information Centric Networking (ICN) have been introduced as emerging technologies for distributing content closer to the end users. The former promises to increase the performance of several applications by using data locality and relieve the core network by addressing the increasing bandwidth demands caused by increased data volume. The latter makes the content directly addressable and routable in the network. Enabling ICN with edge computing in Radio Access Network (RAN) can improve the efficiency of content distribution and communication performance by reducing the distance between users and services. In line with this assertion, in this paper, we propose an ICN-capable RAN architecture for 5G edge computing environments that offers device to device communication and ICN application layer support at base stations. Moreover, ICN and edge caching is only useful for static content-requests for dynamic content have to traverse the core network increasing the latency in 5G networks. To address this issue, we provide a content prefetching strategy based on ICN naming. Experimental results show that our proposed scheme results in high cache hit ratios and lower delays compared to conventional edge systems and prior work on ICN for 5G. (C) 2020 Elsevier B.V. All rights reserved.
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Collections - Graduate School > Software and Communications Engineering > 1. Journal Articles
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