A Novel Probabilistic Flooding Strategy for Unstructured Peer-to-Peer Networks

In this work we propose a novel probabilistic flooding strategy for unstructured p2p networks. Our strategy takes into account the popularity of resources and the hop distance from the node that initiated the query. The latter is used to estimate the number of nodes reached by the query message. Based on the above parameters we adjust the forwarding probability at the time a node receives the query message so as to reduce the duplicate message overhead while maintaining a high probability of query success. The primary goal of our approach is to minimize the cost of search associated with excessive message transmissions. The experimental results support our claims and provide insights into the effect of the above parameters to search performance.