AOTO: adaptive overlay topology optimization in unstructured P2P systems

Abstract

Peer-to-peer (P2P) systems are self-organized and decentralized. However, the mechanism of a peer randomly joining and leaving a P2P network causes topology mismatching between the P2P logical overlay network and the physical underlying network. The topology mismatching problem brings great stress on the Internet infrastructure and seriously limits the performance gain from various search or routing techniques. We propose the adaptive overlay topology optimization (AOTO) technique, an algorithm for building an overlay multicast tree between each source node and its direct logical neighbors so as to alleviate the mismatching problem by choosing closer nodes as logical neighbors, while providing a larger query coverage range. AOTO is scalable and completely distributed in the sense that it does not require global knowledge of the whole overlay network when each node is optimizing the organization of its logical neighbors. The simulation shows that AOTO can effectively solve the mismatching problem and reduce more than 55% of the traffic generated by the P2P system itself.