Unstructured P2P Search Mechanism Based on Ant Colony Optimization

Though flooding-based search mechanism has been used extensively in unstructured peer-to-peer network such as Gnutella, the mechanism is not scalable and as a consequence, it consumes a high amount bandwidths and resources. Because of the strong similarities between self-organizing behaviors of ant colonies and self-organization communications in P2P networks, a search algorithm based on Ant Colony Optimization is presented in this paper. By introducing Ant Colony Optimization, each peer maintains routing table, which stores the amount of pheromone corresponding to classification dropped at the link. Based on the pheromone values, a query is flooded to those peers which are most likely to be resources owner. The update of phenomenon depends on the number of documents found and the link cost in query by all ants’ collective cooperation. Simulation results show that, compared with Modified-BFS mechanism, the search algorithm based on Ant Colony Optimization can effectively improve the search performance, and becomes better than the ModifiedBFS as the peers optimize their routing tables while using a much smaller number of messages.