On probabilistic flooding search over unstructured peer-to-peer networks

Probabilistic flooding has been proposed as a means of reducing the excessive message overheads induced by plain flooding in unstructured peer-to-peer network search. We propose here Advanced Probabilistic Flooding (APF), a novel strategy which operates differently from other known strategies. In particular, the decision of a node to propagate a message (or not) is based on both 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 these 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. Our claims are supported by detailed experiments in various network topologies