Adaptive probabilistic search over unstructured peer-to-peer computing systems

A challenging problem that confronts unstructured peer-to-peer (P2P) computing systems is how to provide efficient support to locate desired files. This paper addresses this problem by using some quantitative information in the form of probabilistic knowledge. Two types of probabilistic knowledge are considered in this paper: overlap between topics shared in the network and coverage of topics at each individual peer. Based on the probabilistic knowledge, this paper proposes an adaptive probabilistic search algorithm that can efficiently support file locating operation in the unstructured P2P network. Then, an update algorithm is devised to keep the freshness of the probabilistic knowledge of individual peers by taking advantage of feedback from the previous user queries. Finally, some extensive experiments are conducted to evaluate the efficiency and effectiveness of the proposed method.