ICN-Based Enhanced Content Delivery for CDN

Lei Gao and Xiaoyong Zhu ()
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Lei Gao: National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, No. 21, North Fourth Ring Road, Haidian District, Beijing 100190, China
Xiaoyong Zhu: National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, No. 21, North Fourth Ring Road, Haidian District, Beijing 100190, China

Future Internet, 2023, vol. 15, issue 12, 1-22

Abstract: With the rapid growth of internet traffic, the traditional host-to-host TCP/IP architecture is subject to many service limitations faced with content-oriented applications. Various novel network architectures have been proposed to solve these limitations, among which Information-Centric Networking (ICN) is one of the most prominent. ICN features the decoupling of content (service) from the physical devices storing (providing) it through location-independent naming, and offers inherent enhancement to network performance, such as multicast and in-network caching. ICN in-network caching has been extensively studied, and we believe that it may also be the main incentive for ISPs to deploy ICN. A CDN (content delivery network) is a typical content-oriented network paradigm that aims to provide the fast delivery of content. In this paper, we leverage the advantages of the in-network caching of ICN to enhance the content delivery efficiency of CDN by integrating ICN as a service. First, we present our design of a content delivery network enhanced with ICN, called IECDN. Additionally, we formulate a mathematical model to optimize the performance of our proposed design and conduct a series of evaluations. The results indicate that our proposed design provides significant performance gains while reducing bandwidth consumption and shows better resilience to traffic surge.

Keywords: CDN; ICN; in-network caching; multi-commodity flow problem (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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