Energy-Efficient Coverage Enhancement Strategy for 3-D Wireless Sensor Networks Based on a Vampire Bat Optimizer

As one of the crucial scenarios of the Internet of Things, wireless sensor networks (WSNs) perform tasks invariably on the basis of the effective cover effect of targets. The cover effect is improved commonly by redeployment of the sensor nodes since they tend to deviate from the optimal deployment location frequently. Given the complex and harsh environment of 3-D WSNs, which impede the recharging and restoration of the batteries of the sensor nodes, the intention of our research is to deal with the multiobjective optimization problem of minimizing total energy consumption and balancing the residual energy based on coverage enhancement during redeployment. By using truncated octahedrons to stack the 3-D environment seamlessly, the coverage enhancement and energy optimization problems are transformed into a task-assignment problem of moving nodes to truncated octahedrons, and an energy-efficient coverage enhancement strategy based on the vampire bat optimizer (VBO) is proposed to solve the above problem, which is inspired by the egoistic and altruistic behavior of vampire bats. the simulation results demonstrate that the proposed strategy can enhance the uniformity of residual energy of nodes by 30.53%, 43.44%, and 32.03% compared to the virtual force-directed particle swarm optimization (VFPSO), the 3-D virtual force algorithm (3DVFA), and the Hungarian algorithm (HA), respectively. Additionally, the proposed strategy can reduce the total energy consumption of nodes and also perform well in terms of energy consumption of the maximum energy consumption nodes, final coverage rate, and time consumption.