Stochastic Analysis of Chain Based File Distribution Architectures with Heterogeneous Peers

Performance analysis of P2P systems is necessary to understand the real impact on the network of such applications. In this paper we study the performance that can be achieved by a simple file distribution architecture in a heterogeneous environment, i.e., when the access links of peers have randomly distributed capacities. The distribution architecture is a chain, where each peer downloads the content from exactly one node and uploads the content to exactly one node. Our analysis starts from a complete knowledge about peers, so that we can derive analytically the deterministic behavior and use the results as reference. We then remove part of the knowledge a peer has about its neighbors and derive the performance that can be obtained in such an environment. Results show that, if peers have sufficient information about neighbors, they can be organized in such a way that slow peers obtain near optimal performance without affecting faster peers. On the other hand, if peers do not know neighbor characteristics, slow peers have a significant impact on global performance, and other, more sophisticated, distribution architectures are required to maintain proper scalability.