State-Based Search Strategy in Unstructured P2P

Efficient resource search in large-scale unstructured peer-to-peer (P2P) systems remains a fundamental challenge. In order to improve search performance, interest-based search is a good way to tackle the challenge. However, the existing interest-based search algorithms pay attention to user interest model and search history, but ignore some influence factors of improving performance. In this paper, through analysis of node´s multi-dimensional quality-of-service (QoS) for search, it is found that node state´s information is essential for improving search performance. So a State-Based Search (SBS) strategy is presented by improving Sripanidkulchai´s interest-based search model, where Node´s state evaluation is based on node´s QoS fuzzification. The SBS enhances the methods of shortcuts adding, ranking and selecting, and state´s life-cycle is predicted by grey theory. The experimental results show that the SBS can improve performance by reducing search response time and achieving load balance.