Genetic algorithm based optimization technique for underwater sensor network positioning and deployment

Abstract

Underwater acoustic sensor networks (UWSNs) are crucial for a multitude of underwater applications that require wireless operation. The deployment of sensor nodes in an optimal arrangement while overcoming the unique challenges posed by the surrounding medium and energy constraints on the sensors is a non-trivial task for real-world applications. As these characteristics are anisotropic with respect to change in temperature, salinity, depth, pH, and transmission frequency, they need to be accounted for in a dynamic simulation to preconfigure a stable physical network layout of nodes. A strategy based on computational intelligence techniques that takes into consideration these factors to achieve a viable configuration with the available resources is of prime importance. The proposed methodology uses a genetic algorithm (GA) based optimization technique for the positioning and deployment of UWSN nodes to maximize the coverage provided to protect a high-value asset (HVA) in a military application. In the case of a civil application for ocean monitoring, the proposed technique is used to identify the minimum number of nodes required and their positions for effective communication.