Structuring peer-to-peer networks using interest-based communities

Interest-based communities are a natural arrangement of distributed systems that prune the search space and allow for better dissemination of information to participating peers. In this paper, we introduce the notion of peer communities. Communities are like interest groups, modeled after human communities and can overlap. Our work focuses on providing efficient formation, discovery and management techniques that can be implemented to constantly changing community structures. We provide a mechanism to generate realistic peer-to-peer network topologies that can be used in simulations that evaluate the operation of our algorithms. Our experiments show how searching the peer-to-peer network can take advantage of peer communities to reduce the number of messages and improve the quality of search results.