Adaptive Search Protocol Based on Optimized Ant Colony Algorithm in Peer-to-Peer Network
In order to solve the low searching efficiency in the peer-to-peer (P2P) network, introduce the ant colony algorithm with the particle swarm optimization in searching procedure. Present a new adaptive search protocol (SACASP) based on the ant colony algorithm with the particle swarm optimization in the Peer-to-Peer Network. The approach simulates the process of the ants’ searching food, and can direct the query routing efficiently according to the adaptive strategy and the positive feedback principle of the pheromone. Decrease the blindness of the messages transmitting in early searching stage by adding the particle swarm optimization to the ant colony algorithm. Give the adaptive P2P search model based on the fusion algorithm, and design the data structure and steps of the model. The simulation experiment shows, PSACASP can effectively shorten the time and reduce the search query packets comparing with the other search algorithms, and it can achieve better search performance and decrease the network loads.