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

fYear

2009

fDate

5-7 Aug. 2009

Firstpage

1751

Lastpage

1755

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICAL.2009.5262666

Filename

5262666