Result Analysis of Implementing Bacterial Foraging Technique and Genetic Algorithm in Sensor Deployment

One of the prominent factors to reduce overlapping area among any deployment of sensors is to choose an algorithm with perfect parameters. In this research, two algorithms named as Bacterial Foraging Optimization and Genetic algorithm is studied to get the better results by comparing the outputs. Fitness functions along with coverage both are analyzed in detail. It is found that Bacterial technique works more effectively as compared to Genetic. Both techniques have been already implemented to deploy several networks such as internet in metropolitan cities and many more. Some organizations prefer these algorithms for different purposes such as to reduce overlapping of area, to get cost effectiveness. Both have been proved very efficient in specific performances. The main purpose of this research is to compare the performance in a same network to make decision about the use of these for deployment.