Coverage and Connectivity Aware Deployment Scheme for Autonomous Underwater Vehicles in Underwater Wireless Sensor Networks

Abstract

For efcient monitoring of marine environments using underwater wireless sensor net works (UWSNs), a fundamental issue is to maximize network coverage as well as connec tivity by appropriate deployment of the nodes within a given sensing area. Most of the existing node deployment schemes proposed for UWSNs, assume that sensor nodes are static and their location after deployment are fxed. However, due to ocean current and the contact of the underwater creatures, these deployed static sensor node moves from its original locations to other locations, which disrupts the network connectivity with the base stations as well as most of the targets remain uncovered. To fnd a solution to this issue, authors propose a coverage and connectivity aware deployment scheme for optimal place ment of a set of autonomous underwater vehicles (AUVs) within UWSNs. The proposed scheme uses an improved Non-dominated Sorting Genetic Algorithm-II based metaheuris tic technique with a novel ftness function which contains three parameters namely cov erage quality, connected cost and network lifetime. Further, proposed scheme applies an efective encoding scheme for the population representation and devises a novel ftness function for upgrading the quantity of the AUVs as well as their location. Performance esti mation of the proposed scheme and its comparison with the existing schemes with respect to convergence rate, coverage quality, connected cost, average energy consumption and network lifetime are discussed in detail. The simulation outcome confrm that the proposed approach upgrades the coverage of the network.