Efficient search using adaptive metadata spreading in peer-to-peer networks

Abstract

Search is until now a difficult problem in peer-to-peer (P2P) filesharing systems. In this paper, we propose to use adaptive metadata spreading to make search in P2P networks efficient and scalable to large-scale systems. We model the search process in unstructured P2P networks obtain the optimized metadata populations for performance optimization. Based on the model, we propose adaptive metadata spreading approach which can adapt metadata populations to variational environment and achieve the optimized search performance. To implement our approach in fully decentralized P2P system, we employ self-organized fault-tolerant overlay trees, through which peers can easily cooperate with each other to perform adaptive metadata spreading with minor overhead. © Springer-Verlag 2004.