Underwater Self Deployment of Wireless Sensors for Maximum Coverage and Connectivity using K-Means Clustering

Abstract

By virtue of abundant research being executed in terrestrial wireless sensor networks, we get enlightened about the different advantages of using wireless sensors and implemented these wireless sensors in underwater to probe the area below the sea for its various applications. The most crucial task in underwater 3D space is the node deployment such that sensors can cover the maximum area while simultaneously maintaining the connectivity with the base station. Due to the advantages of self deployment where no pre calculations and no human interventions are needed, we proposed a distributed move restricted self deployment underwater wireless sensor network. The main emphasis is on maximizing the coverage area by the sensor nodes and simultaneously maintaining the connectivity with the base station. Firstly, the maximum coverage has achieved by removing the interference between the sensor nodes which minimize the coverage overlap and thus more area can be covered which improves the network coverage. Then by using K-Means clustering, all the sensors nodes were divided into clusters, having one centroid for each cluster. Further all these centroids have been interconnected and then by finding the centroid which is nearest to the sink by Euclidean distance formula, we connect it to the sink.