Performance Comparison of WSN &WSAN using Genetic Algorithm

AbstractA wireless sensor network (WSN) consists of two sets of nodes: sensors and actors, where the set of sensors performs all the sensing (data collection) from their surrounding environment. Since sensors operate by batteries, then they are limited with their processing and communication capabilities due to the short life-span of the batteries. On the other hand, the set of actors has more capabilities with extended life-span batteries, and their roles are to collect and process the raw data from the sensors to determine the next action for WSN. The actor placement problem is to select a minimal set of actors and their optimal locations in WSN keeping in mind the communication requirements between sensors and actors. We have encoded the actor placement problem into the evolutionary approach, where the objective function is to find the minimal total number of actors covering as many sensors as possible to improve the performance of WSN. The experimental results demonstrate the feasibility of our evolutionary approach in covering 77% of 61 sensors by three actors and its performance is compared for various parameters