Maximum Likelihood Estimation of Peers’ Performance in P2P Networks

The problem of encouraging trustworthy behavior in P2P online communities by managing peers’ reputations has drawn a lot of attention recently. However, most of the proposed solutions exhibit the following two problems: huge implementation overhead and unclear trust related model semantics. In this paper we show that a simple probabilistic technique, maximum likelihood estimation namely, can reduce these two problems substantially when employed as the feedback aggregation strategy. Thus, no complex exploration of the feedback is necessary. Instead, simple, intuitive and efficient probabilistic estimation methods suffice.