Can Online Social Friends Help to Improve Data Swarming Performance?

Abstract

We investigate whether friend relationship in online social networks (OSNs) can help to improve the performance of Peer-to-Peer (P2P) data swarming systems. Due to the importance and popularity of OSNs and P2P swarming (the two major applications on the Internet), the research community shows increasing interest in leveraging OSNs for data swarming system design. In this paper, we present our initial findings about some of the basic issues in this emerging area, which are largely missing from existing work. Specifically, we conduct a measurement study of a popular online social network -- Douban, 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 simple public social streaming scheme that lets peers simultaneously join multiple swarms of the same data content with the help from their online social friends. Our simulation studies demonstrate that this social scheme can lead to significant performance improvement in vanilla P2P streaming systems. Furthermore we explore the impact of various social graphs on the performance improvement brought about by the social scheme. Our findings indicate that our proposed social 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 the empirical Facebook and Douban social graphs. This result points to an important research direction of leveraging OSNs in data swarming system design.