A Biased k-Random Walk to Find Useful Files in Unstructured Peer-to-Peer Networks

Abstract

In this paper, we consider a problem of finding "useful" files matching a given query in unstructured P2Ps. The proposed scheme is a variant of k-random walk, which combines a synchronization mechanism proposed by Lv et al. with a mechanism to evaluate the usefulness of discovered files. In addition, we apply a variant of popularity-biased k-random walk to accelerate the file search in normal k-random walk under uniform distribution. The goodness of the scheme is evaluated by simulation. The result of simulations indicates that the proposed biased k-random walk scheme certainly finds useful files in short time, without significantly increasing the number of message transmissions.