A Novel Sensor Deployment Approach Using Fruit Fly Optimization Algorithm in Wireless Sensor Networks

The sensor deployment is a fundamental problem in wireless sensor networks(WSN), the performance of WSN largely depends on a good sensor deployment scheme. In this paper, we present a novel sensor deployment scheme based on fruit fly algorithm(FOA) to improve the coverage rate. Each fruit fly represents a solution for sensor deployment independently, and they are given the random direction and distance for finding food using osphresis. Then we find out the fruit fly with the highest smell concentration judgment value from the fruit fly group and keep its positions, and then the fruit fly group will fly towards that position by using their sensitive vision. We have done simulations both in the ideal and obstacle areas, FOA-based sensor deployment is compared with the classic standard PSO and the novel GSO, simulation results show the effectiveness of the proposed approach.