Energy-efficient models for coverage problem using sensors with adjustable sensing ranges

In wireless sensor networks, density control is a promising approach that has a considerable impact on extending the network lifetime. To optimize the energy utilization, the sensors in active mode adjust their sensing ranges to fulfill two conflicting objectives, minimizing the overlapping sensing area of the sensors and at the same time maintaining a high degree of coverage. In this paper, we consider the problem of energy-efficient area coverage by adopting various node scheduling models for sensor networks with adjustable sensing ranges. We construct a universally elemental pattern that can adapt its topology form to generate a set of new energy-efficient models, since recent exploration of node scheduling models has not been conducted in a systematic manner. Mathematical results and extensive simulation highlight important remarks for practical applications and show that the new models outperform existing ones in terms of energy efficiency.