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Range-Based Localization in Underwater Wireless Sensor Networks Using the Optimization Algorithm
Nishi Yadav and Vishnu Prasad Yadav

Underwater wireless sensor networks (UWSNs) are made up of several underwater wireless sensor nodes that are scattered throughout the marine environment and can be utilized for resource discovery, navigation, surveillance, data collecting, and disaster prediction. Energy efficiency becomes a significant issue in the UWSN’s design due to the use of limited battery capacity and the difficulties of changing or charging the inbuilt batteries. To overcome the energy efficiency problem in routing, a hybrid approach is developed in this study for UWSNs. Initially, a Range-based Localization technique was used to locate sensor nodes, which used the received signal intensity and arrival time to provide reliable node range estimation. Accordingly, this work presents a Recursive Position Estimation (RPE) technique, which determines the sensor location for a given number of available anchor references. A path must be built between a sensor (or source) and the desired destination (or surface sink) for effective and reliable data transmission. Between the sensor nodes, a multi-hop communication channel is conceivable. The intermediate nodes deliver the packet data until it reaches the sink node in multi-hopping. To route packet data towards the destination, an Artificial Bee Colony (ABC) integrated Chaotic Particle-swarm Krill Herd (ABC-CPKH) technique is used, as the main contribution deals with the choice of cluster head. Due to the harsh underwater environment, its capabilities, and the open acoustic channel is vulnerable to threats and malicious attacks. The research suggested a Delphi detection system to reduce the threat problem in UWSN, which prevents undesired packets from being delivered to the destination, mainly, it prevents the data from the wormhole attack. PDR, end-to-end delay, energy consumption, network lifetime, localization energy, localization coverage, detection rate, etc., are performance metrics for the proposed study, which is simulated using Python software. The proposed method is compared to the existing IRL-WOA, EECRP, and DSIP methods, Compared to these methods, the proposed method provided 6%, 3.5% and 4% better performance for time complexity, energy consumption and delay. Consequently, future research can suggest new metaheuristic algorithms to more efficiently allocate resources and increase localization accuracy, respectively.

Keywords: Region-Based Localization, UWSNs, RSS, TOA, Recursive Position Estimation, Hybrid Algorithm, Cluster Head Selection, Routing Protocol, Delphi Detection, and Wormhole Attack