Peer-to-Peer File Sharing Based on Network Coding

Abstract

Network coding is a promising enhancement of routing to improve network throughput and provide high reliability. It allows a node to generate output messages by encoding its received messages. Peer-to-peer networks are a perfect place to apply network coding due to two reasons: the topology of a peer-to-peer network is constructed arbitrarily, thus it is easy to tailor the topology to facilitate network coding; the nodes in a peer-to-peer network are end hosts which can perform more complex operations such as decoding and encoding than simply storing and forwarding messages. In this paper, we propose a scheme to apply network coding to peer-to-peer file sharing which employs a peer-to-peer network to distribute files resided in a web server or a file server. The scheme exploits a special type of network topology called combination network. It is proved that combination networks can achieve unbounded network coding gain measured by the ratio of network throughput with network coding to that without network coding. The scheme encodes a file into multiple messages and divides peers into multiple groups with each group responsible for relaying one of the messages. The encoding scheme is designed to satisfy the property that any subset of the messages can be used to decode the original file as long as the size of the subset is sufficiently large. To meet this requirement, we first define a deterministic linear network coding scheme which satisfies the desired property, then we connect peers in the same group to flood the corresponding message, and connect peers in different groups to distribute messages for decoding. Moreover, the scheme can be readily extended to support topology awareness to further improve system performance in terms of throughput, reliability and link stress. Our simulation results show that the new scheme can achieve 15%-20% higher throughput than Narada which does not employ network coding. In addition, it achieves good reliability and robustness to link failure or churn.