RSB-Topo: A Topology Adaptation Algorithm for Unstructured P2P Networks

Abstract

Peer-to-Peer (P2P) technology has been widely applied in today's Internet. Unstructured P2P systems, where peers connect with each other to form dynamic, flexible and scalable networks, are commonly used for resource sharing. Resource location in unstructured P2P systems tends to use "blind search" strategies (i.e. flooding and random walk) for its simplicity and low maintenance cost. However, due to lack of location information, the performance of "blind search" is heavily relied on the network topology. Topology adaptation, by properly adjusting the topology of the P2P overlay network, is a promising approach to improve the search performance. In this paper, we use Relative Search Betweenness (RSB) to estimate nodes' search ability. A RSB-based topology adaptation algorithm (RSB-Topo) is proposed, where peers spontaneously adjust their connections to achieve better performance. Simulation results show that our algorithm could greatly increase search success rate and search coverage, and also decrease response delay to improve the search performance in unstructured P2P networks.