wireless sensor network design through genetic algorithm

in this paper, we study wsn design, as a multi-objective optimization problem using ga technique. we study the effects of ga parameters including population size, selection and crossover method and mutation probability on the design. choosing suitable parameters is a trade-off between different network criteria and characteristics. type of deployment, effect of network size, radio communication radius, density of sensors in an application area, and location of base station are the wsn’s characteristics investigated here. the simulation results of this study indicate that the value of radio communication radius has direct effect on radio interference, cluster-overlapping, sensor node distribution uniformity, communication energy. the optimal value of radio communication radius is not dependent on network size and type of deployment but on the density of network deployment. location of the base station affects radio communication energy, cluster-overlapping and average number of communication per cluster head. bs located outside the application domain is preferred over that located inside. in all the network situations, random deployment has better performance compared with grid deployment.