The implementation of optimization algorithm for energy efficient dynamic ad hoc Wireless Sensor Networks

Mohaned Al Obaidy*, Aladdin Ayesh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

2 Citations (Scopus)

Abstract

In this work we are presenting the implementation part of our research which explores two of the main Evolutionary Computation techniques which are; Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) to optimize the energy dissipation in a dynamic Wireless Sensor Network (WSN). We are evolving a hybrid algorithm by applying the GAs in the first phase to divide the sensor network into K-clusters (K-unknown). The output of the first phase will be used as an initial population for the particles in the Swarm which represents the dynamic Sensor Network. GAs proved to be used effectively in the optimization of static Sensor Networks, but for dynamic networks, PSO algorithms are more suitable since the swarms are moving objects by nature. Hence, in this work PSO algorithms are proposed to keep the optimum distances between the sensor nodes during the sensors movement.

Original languageEnglish
Title of host publicationAdaptive and Emergent Behaviour and Complex Systems
Subtitle of host publicationProceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB 2009
Pages16-22
Number of pages7
Publication statusPublished - 2009
Externally publishedYes
Event23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB 2009 - Edinburgh, United Kingdom
Duration: 6 Apr 20099 Apr 2009

Conference

Conference23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB 2009
Country/TerritoryUnited Kingdom
CityEdinburgh
Period6/04/099/04/09

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