Optimized Distance Vector Hop Localization Based on Pelican Optimization Algorithm in Underwater Wireless Sensor Networks

Abstract

In recent days, underwater exploration has emerged as one of the most predominant technologies for enhancing surveillance and early warning systems. Finding the location of the nodes placed in underwater is a difficult task owing to its harsh underwater environment. In large underwater wireless sensor networks (UWSNs), pinpointing the exact coordinates of sensor nodes may not be feasible or be incredibly expensive. In most of the applications, the coarse coordinate of the node is adequate. The primary technique used in UWSNs to determine the location of sensor nodes, based on the average distance between hops, is referred to as distance vector-hop (DV-Hop) localization. Nevertheless, the positioning accuracy in the classic DV-Hop technique is influenced by the average hop distance. To reduce the localization error, it is possible to create a distinct and optimized DV-Hop approach. To improve the effectiveness of the localization process, the average distance between hops is primarily used as an objective function. The optimization of this objective function is achieved by employing the Pelican Optimization Algorithm (POA). There is a noticeable decrease in the localization discrepancy if the optimized average hop distance is used to precisely determine the unidentified node to the anchor node distance among them. The factors used to evaluate the ability of the proposed methodology are the ratio of anchor, transmission range, and the density of the node. Compared to other localization procedures, the obtained outcomes demonstrate that the optimized approach that has been suggested achieves a low localization error of 0.3.