Analyzing Effects of Social Media User's Influence on Contents Caching in ICN

• Published in: IEEE access Vol. 11; p. 1
• Main Authors: Honda, K., Nakamura, R., Kamiyama, N.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cache network; Cache storage; Caching; Information science; Information-centric networking; Internet; Knowledge engineering; Mathematical analysis; Performance analysis; Servers; social network; Social networking (online); Social networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2023.3330850

In recent years, with the rapid growth of Social Networking Service (SNS), Information-Centric Networking (ICN) has been emerged as a promising network architecture for mitigating the traffic generated by SNS users. To fully utilize potential of ICN as a sort of the cache network, we have to carefully design the caching strategy and the cache-replacement policy while considering both of features of social network among SNS users and those of cache network. Therefore, in this paper, we assume that ICN is introduced as a content distribution infrastructure for SNS, and extensively analyze the characteristics of the socially-aware ICN. In particular, we focus on the influential user called influencer, which is one of typical features of social networks, and investigate the effect of the selection of influential users and their ratio on the content caching in ICNs. Our key findings are summarized as follows. First, the effectiveness of the content caching is dominated by the centrality measures to determine influential users. Second, on determining influential users, it is enough to sample at most 30% of the social network rather than its entire structure. Third, to gain the benefit of the content caching, we have to carefully select the ratio of influential users on the social network whose degree distribution follows power-law.