An Efficient Method Based on Genetic Algorithms to Solve Sensor Network Optimization Problem
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, the authors 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, they can greatly minimize the total communication distance, thus prolonging the network lifetime. Simulation results show that the algorithm can quickly find a good solution.