Leveraging online social friendship to improve data swarming performance

Abstract

We investigate whether social friend relationship on online social networks (OSNs) can help to improve the performance of Peer-to-Peer (P2P) data swarming systems such as P2P streaming and file sharing networks. Due to the importance and popularity of OSNs and P2P swarming, the research community shows increasing interest in leveraging OSNs to improve data swarming performance. We present in this paper our findings on a few fundamental research issues in this emerging area, which are largely missing from existing work. Specifically, we conduct a measurement study of Douban, a popular online social network that hosts a large amount of user reviews on movies, and our analysis of this OSN provides strong empirical evidence of the association between users’ content interests and their online social friend relationship. Then we introduce a social scheme that lets peers simultaneously join multiple swarms of identical data content with the help from their online social friends. We demonstrate that this social scheme can result in significant performance improvement in both P2P streaming and file sharing systems. Furthermore, we explore the impact of various social graphs on the performance improvement of P2P streaming brought about by the social scheme. Our findings indicate that the scheme consistently achieves greater performance improvement on Erdos–Renyi’s random graphs than on other graphs such as Barabasi-Albert’s scale-free graphs and two social graphs empirically sampled from Facebook and Douban OSNs. Our results point to several important research directions of leveraging OSNs in data swarming system design.