Knowledge and Cache Based Adaptive Query Searching in Unstructured P2P Networks
Efficient search is a challenging task in unstructured peer-to-peer networks. In this paper, Knowledge and Cache based Adaptive Query Searching (KCAQS) is proposed that adaptively performs a query searching through either directed flooding or biased random walk based on the number of hop counts in query message. In addition, knowledge intended forwarding is deployed for forwarding a query to the high quality peers through probabilistic knowledge predicted from the previously requested queries. Searched results are properly cached in the peers along the returning path. Synchronized caching is performed to properly update the responses of each peer to its connected corresponding high degree connectivity peer in the overlay network.