Small World Based Adaptive Probabilistic Search (SWAPS) for Unstructured Peer-to-Peer File Systems

One of the essential problems in P2P is the strategy for resource discovery. Related methods in unstructured P2P systems either depend on the flooding and its variations or utilize various indices, which results in too much traffic load to forward messages or too expensive cost to maintain the indices. Presented in this paper is an adaptive, bandwidth-efficient and easy to maintain search algorithm for unstructured P2P file systems—small world based adaptive probabilistic search (SWAPS). In SWAPS, the users' access interest attributes are mined based on ontology tree. And following the behavior patterns of users, interest attributes based small world overlay network is spontaneously constructed. The key factors influencing the locating performance in SWAPS are also analyzed and efficient routing algorithm (interest rank based, ontology distance based and interest breadth based) is designed. And the final simulation experiment shows that the small world based locating algorithm in unstructured P2P can remarkably improve the search efficiency with the small average path length, high success rates, very low bandwidth consumption and the eminent adaptability to access behaviors of the users.