An Energy-Conscious Surveillance Scheme for Intrusion Detection in Underwater Sensor Networks Using Tunicate Swarm Optimization

Abstract

The underwater environment is crucial for various scientific applications, including naval bases, offshore installations, and military surveillance. Precise intruder detection in such environments via underwater acoustic sensor networks (UASN) with minimal network resources is quite challenging in safeguarding the territorial marine environment. Moreover, the unavailability of GPS, poor visibility, and diverging network scenarios make it more complicated than terrestrial sensor networks. Hence, this article addresses an energy-efficient surveillance scheme using only one beacon -node for intrusion detection subject to location precision, energy restrictions, and network overhead constraints. The proposed energy-conscious surveillance scheme monitors the chosen region of interest (ROI) with a single beacon node using its Boolean perception probability to find an intruder node in its area of responsibility. Next, a low-cost centroid technique is applied to calculate the estimated location coordinates of the intruder node. Estimated intruder coordinates are further enhanced using a rapid convergent Tunicate swarm algorithm (TSO). Thorough findings from simulations reveal that the proposed technique reduces the overhead of employing numerous beacon nodes while substantially improving the intruder position accuracy compared to its contemporary schemes.