Title :
Research on peer-to-peer network search algorithm based on improved ant colony optimization
Author :
Gao, Zhengzhong ; Liu, Longji ; Zhang, Songmei
Author_Institution :
Coll. of Inf. & Electr. Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
Abstract :
How to reduce the number of messages or improve searching efficiency has been a key problem which restricts the expanding of decentralized and unstructured P2P (peer-to-peer) networks. Based on traditional ant colony optimization (ACO) principle, this paper proposes a new algorithm for unstructured P2P networks by using the pheromone which can reflect the distribution of different types of files. The algorithm can reduce the produced message packets and reach better searching efficiency than the traditional Ant methods do in P2P network.
Keywords :
optimisation; peer-to-peer computing; search problems; dynamic file category; improved ant colony optimization; peer-to-peer network search algorithm; unstructured P2P network; Ant colony optimization; Automation; Circuit simulation; Educational institutions; Evolutionary computation; Floods; Logistics; Peer to peer computing; Routing; Simulated annealing; P2P network; ant colony optimization; dynamic file category; pheromone;
Conference_Titel :
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-4794-7
Electronic_ISBN :
978-1-4244-4795-4
DOI :
10.1109/ICAL.2009.5262666
