Multi-objective peer-to-peer neighbor-selection strategy using genetic algorithm

Authors:
Ajith Abraham;Benxian Yue;Chenjing Xian;Hongbo Liu;Millie Pant
Affiliations:
Centre for Quantifiable Quality of Service in Communication Systems, Norwegian University of Science and Technology, Trondheim, Norway and School of Computer Science, Dalian Maritime University, D ...;Department of Computer, Dalian University of Technology, Dalian, China;School of Computer Science, Dalian Maritime University, Dalian, China;Department of Computer, Dalian University of Technology, Dalian, China and School of Computer Science, Dalian Maritime University, Dalian, China;Department of Paper Technology, Indian Institute of Technology-Roorkee, Saharanpur, India
Venue:
HiPC'07 Proceedings of the 14th international conference on High performance computing
Year:
2007

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Abstract

Peer-to-peer (P2P) topology has significant influence on the performance, search efficiency and functionality, and scalability of the application. In this paper, we present a Genetic Agorithm (GA) approach to the problem of multi-objective Neighbor Selection (NS) in P2P Networks. The encoding representation is from the upper half of the peer-connection matrix through the undirected graph, which reduces the search space dimension. Experiment results indicate that GA usually could obtain better results than Particle Swarm Optimization (PSO).