Hybrid optimization for fault‐tolerant and accurate localization in mobility assisted underwater wireless sensor networks

Abstract

SummaryMobility prediction and fault tolerance are extremely difficult due to underwater characteristics. Energy drain is one of the major causes for node faults. Hence, in this research article, a hybrid optimization algorithm is developed for fault‐tolerant and accurate localization in UWSN. In this technique, Artificial Butterfly Optimization (ABO) algorithm is applied for finding the distance between the anchors and the sensors. Each non‐localized node runs ABO algorithm for finding the distance amid the anchor or beacon nodes. Then, applying Quaternion‐based Backtracking Search Optimization (QBSA) algorithm, non‐localized sensor nodes are localized and to decrease the localization error based on the Received Signal Strength Indicator (RSSI), battery energy, and distance parameters. Aqua‐Sim a tool kit of NS2 is an open‐source software developed for Underwater Wireless Sensor Network research, and this proposed algorithm will be implemented using this software. By simulation results, it is shown that the proposed optimization algorithm reduces the localization error, latency, and cost and energy consumption.