Genetical Swarm Optimization of Multihop Routes in Wireless Sensor Networks. (29th November 2010)

• Record Type: Journal Article
• Authors: Caputo, Davide; Grimaccia, Francesco; Mussetta, Marco; Zich, Riccardo E.
• Other Names: Hong Tzung P. Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2010(2010)
• Publication Date: 2010-11-29
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2011/523943
• Languages: English
• ISSNs: 1687-9724

Abstract

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.