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Applied Computational Intelligence and Soft Computing
Volume 2017, Article ID 4169152, 17 pages
https://doi.org/10.1155/2017/4169152
Research Article

Parallel Evolutionary Peer-to-Peer Networking in Realistic Environments

Graduate School of Computer Science and System Engineering, Kyushu Institute of Technology, Kawazu 680-4, Iizuka, Fukuoka 820-8502, Japan

Correspondence should be addressed to Kei Ohnishi; pj.ca.hcetuyk.esc@ihsinho

Received 6 July 2016; Accepted 28 December 2016; Published 26 January 2017

Academic Editor: Shyi-Ming Chen

Copyright © 2017 Kei Ohnishi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In the present paper we first conduct simulations of the parallel evolutionary peer-to-peer (P2P) networking technique (referred to as P-EP2P) that we previously proposed using models of realistic environments to examine if P-EP2P is practical. Environments are here represented by what users have and want in the network, and P-EP2P adapts the P2P network topologies to the present environment in an evolutionary manner. The simulation results show that P-EP2P is hard to adapt the network topologies to some realistic environments. Then, based on the discussions of the results, we propose a strategy for better adaptability of P-EP2P to the realistic environments. The strategy first judges if evolutionary adaptation of the network topologies is likely to occur in the present environment, and if it judges so, it actually tries to achieve evolutionary adaptation of the network topologies. Otherwise, it brings random change to the network topologies. The simulation results indicate that P-EP2P with the proposed strategy can better adapt the network topologies to the realistic environments. The main contribution of the study is to present such a promising way to realize an evolvable network in which the evolution direction is given by users.