Alternative Performance Metrics And Optimal Strategies For Peer-To-Peer File Dissemination Networks

Abstract

Peer-to-peer (P2P) file distribution is a scalable way to disseminate content to a wide audience. For a P2P network, one fundamental performance metric is the average time needed to deliver a certain file to all peers, which in general depends on the topology of the network and the scheduling of transmissions. Despite its apparent importance, how to minimize average finish time remains an open question even for a fully-connected network. This is mainly due to the analytical challenges that come with the combinatorial structures of the problem. In this thesis, by using the water-filling technique, we determine how each peer should use its capacity to sequentially minimize the file download times in an upload-constrained P2P network. Furthermore, it is shown that this scheduling also minimizes average finish time for the network. This optimality result not only provides fundamental insight to scheduling in such P2P systems, but also can serve as a benchmark to evaluate practical algorithms and illustrate the scalability of P2P networks. An overview of existing P2P systems is given, analytical challenges posed by the inclusion of download constraints are considered, and further areas for research in P2P optimality are discussed.