Localization Problem Solution Using K-Mean Clustering and Bacterial Foraging Optimization in Wireless Sensor Network

Wireless Sensor Networks (WSN) popularity has increased tremendously in recent time due to growth of semiconductor and VLSI technology. WSN has the potentiality to connect the physical world with the virtual world by forming a network of sensor nodes. Here, sensor nodes are usually battery-operated devices, which operate in harsh environment. So, hence energy saving of sensor nodes is a major problem which should be implemented by considering various communication parameters like path loss, attenuation and power received. In Wireless Sensor Networks (WSN) also named Mobile ADHOC network (MANET), the sensors or the mobile transceivers are randomly deployed in the sensor field which brings the problem of coverage for all or some of the nodes. As the coverage problem can increase overall effective distance of all nodes from the sensor which further affects the fitness function which depends upon attenuation, path loss, power received which further effects overall throughput of the system. It is a unique problem and in maximizing coverage, the sensors need to be placed in a position such that the sensing capability of the network is fully utilized to ensure high quality of service. The main objective of the paper is to find optimum location of sensors and find the minimum distance between nodes and sensors. And the value of fitness function should be maximum for nodes and sensors. Keywords-: wireless sensor network ; K-mean clustering, BFO, fitness function, comparison