Genetical Swarm Optimization of Multihop Routes in Wireless Sensor Networks

• Main Authors: Davide Caputo, Francesco Grimaccia, Marco Mussetta, Riccardo E. Zich
• Format: Article
• Language: English
• Published: Hindawi Limited 2010-01-01
• Series: Applied Computational Intelligence and Soft Computing
• Online Access: http://dx.doi.org/10.1155/2010/523943

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.