Efficient randomized search algorithms in unstructured Peer-to-Peer networks (original) (raw)

Searching for objects in unstructured peerlo-peer (P2P) networks is an important problem, and one that has received recent attention. In this paper, we present a simple, elegant, yet highly effective technique for object location (including rare objects). Our scheme installs object references at a known numhu of randomly selected peers. A query to the object is routed to a prede-Icnnined number of random peers, selected independently of (he installation procedure. The high probability of a non-empty intersection between these two sets forms the basis for our search mechanism. We prove analyticnUy, and demonstrate experimentally, that our scheme provides high probabilistic guarantees of success, while incurring minimal overhead. EITedive realiz.ation of the approach builds on a number of recent results on generating random walks, and efficiently estimating network size for unstructured networks. The presence of failures (departures) in the network pose additional challenges. Finally, effective strategies for installing references (0 replicas are critical for optimizing the lradeoffbetween installation overhead and search lime. We address these issues in an analytical framework and validate our results on a variety of real and synthetic topologies. Our results generalize to related problems of estimating and controlling object replication, and eliminaling duplicates in large-scale unstructured networks.