Target Tracking Scheme Using Multi-Objective Differential Evolution for Underwater Wireless Sensor Networks

In underwater wireless sensor networks (\({\text{UWSNs}}\)), sensor allocation is a vital issue for target tracking applications. Sensor nodes are used to track the particular target in the predefined region. But, some targets are not covered because of the fewer sensor nodes, limited energy and random deployment. In the existing literature, most of the researchers have used static nodes which diminished the energy consumption of the network. However, due to harsh water and underwater habitat, mobile nodes are also displaced from their actual position and get stuck. Thus, the mobile node is unable to track the particular target which disrupts the network stability. So, we have to choose an optimal set of mobile nodes to strengthen energy efficiency and network lifetime. Hence, we have proposed the target tracking scheme through multi-objective differential evolution (\({\text{MODE}}\)) in \({\text{UWSNs}}\). This scheme incorporates the crossover operator with the non-dominated sorting approach. It is applied to balance the diversity in the population set with a high convergence rate. Fitness function is also described with packet delivery probability (\(PDP\)) and residual energy over distance to determine the best mobile node in the direction of the target. The proposed scheme dominates the existing one in terms of the percentage of the allocated nodes, consumed energy and network lifetime.