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Applied Computational Intelligence and Soft Computing
Volume 2010 (2010), Article ID 523943, 14 pages
http://dx.doi.org/10.1155/2010/523943
Research Article

Genetical Swarm Optimization of Multihop Routes in Wireless Sensor Networks

Politecnico di Milano, Dipartimento di Energia, Via La Masa, 34, I-20156 Milano, Italy

Received 19 March 2010; Revised 4 August 2010; Accepted 9 November 2010

Academic Editor: Tzung P. Hong

Copyright © 2010 Davide Caputo et al. 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 recent years, wireless sensor networks have been attracting considerable research attention for a wide range of applications, but they still present significant network communication challenges, involving essentially the use of large numbers of resource-constrained nodes operating unattended and exposed to potential local failures. In order to maximize the network lifespan, in this paper, genetical swarm optimization (GSO) is applied, a class of hybrid evolutionary techniques developed in order to exploit in the most effective way the uniqueness and peculiarities of two classical optimization approaches; particle swarm optimization (PSO) and genetic algorithms (GA). This procedure is here implemented to optimize the communication energy consumption in a wireless network by selecting the optimal multihop routing schemes, with a suitable hybridization of different routing criteria, confirming itself as a flexible and useful tool for engineering applications.