Probabilistic Knowledge Discovery and Management for P 2 P Networks

The Peer-to-Peer (P2P) paradigm dictates a distributed network model which enables the sharing of resources between its participants. In many cases, the location of these resources is a non-trivial task with network-wide effects. In this work, we describe the Adaptive Probabilistic Search method (APS) for search in unstructured P2P networks. APS utilizes feedback from previous searches to probabilistically guide future ones. Besides being a very cost-efficient technique, it enables the distribution and adaptation of search knowledge over the network. Based on that, we provide examples where this scheme can prove useful in more demanding environments.

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