Minimization of the number of cluster heads in a wireless sensor network is a very important problem to reduce channel contention and to improve the efficiency of the algorithm when executed at the level of cluster-heads. In this paper, we propose an efficient method based on genetic algorithms (GAs) to solve a sensor network optimization problem. Long communication distances between sensors and a sink in a sensor network can greatly drain the energy of sensors and reduce the lifetime of a network. By clustering a sensor network into a number of independent clusters using a GA, we can greatly minimize the total communication distance, thus prolonging the network lifetime. Simulation results show that our algorithm can quickly find a good solution.
@article{arxiv.1104.0355,
title = {An Efficient Method Based on Genetic Algorithms to Solve Sensor Network Optimization Problem},
author = {Ehsan Heidari and Ali Movaghar},
journal= {arXiv preprint arXiv:1104.0355},
year = {2011}
}