In recent years, there has been growing interest in the effective operation of anycast Content Delivery Networks (CDN). Existing anycast CDNs answer the same set of cache servers (CSes) for all content requests without considering the geographical distribution of popularity of contents. It has also been reported that the appropriateness of the selection of delivery servers decreases as the number of servers assigned to the same IP address increases in anycast delivery. To solve these problems, we propose a new anycast distribution method that incorporates the spatial locality of the popularity of content. Specifically, we propose an algorithm that creates multiple CS sets consisting of a small number of CSs and assigns the optimal CS set to each content by minimizing the number of CSes in the CS set. The algorithm aims to reduce the dispersion of delivery delay by minimizing the number of CSes in the CS set, while covering a wide range of countries. Using a genetic algorithm, we construct CS sets that incorporates spatially biased ASes and verify its effectiveness through computer simulation. Numerical evaluation results show that the proposed method can effectively cover ab out 80% of requests of highly popular content with about 15 ASes. It is expected that the proposed method can effectively cover the requirements for most of the contents with a small number.
Short bio:
Noriaki Kamiyama received his M.E. and Ph.D. degrees in communications engineering from Osaka University in 1994 and 1996, respectively. From 1996 to 1997, he was with the University of Southern California as a visiting researcher. He joined NTT Multimedia Network Laboratories in 1997, and he has been at NTT Network Technology Laboratories by 2016. He was also with the Osaka University as an invited associate professor from 2013 to 2014 and an invited professor in 2015. From 2017, he has been a professor of Fukuoka University. From 2021, he is a professor of Ritsumeikan University. He has been engaged in research concerning content distribution systems, network design, network economics, traffic measurement and analysis, and traffic engineering. He received the best paper award at the IFIP/IEEE IM 2013. He is a member of IEEE, ACM, and IEICE.