Probabilistic Field Coverage using a Hybrid Network of Static and Mobile Sensors

Providing field coverage is a key issue in many sensor network applications. For a field with unevenly distributed static sensors, a quality coverage with acceptable network lifetime is often difficult to achieve. We propose a hybrid network that consists of both static and mobile sensors, and we suggest that it can be a cost-effective solution for held coverage. The main challenges of designing such a hybrid network are, first, determining necessary coverage contributions from each type of sensors; and second, scheduling the sensors to achieve the desired coverage contributions, which includes activation scheduling for static sensors and movement scheduling for mobile sensors. In this paper, we offer an analytical study on the above problems, and the results also lead to a practical system design. Specifically, we present an optimal algorithm for calculating the contributions from different types of sensors, which fully exploits the potentials of the mobile sensors and maximizes the network lifetime. We then present a random walk model for the mobile sensors. The model is distributed with very low control overhead. Its parameters can be fine-tuned to match the moving capability of different mobile sensors and the demands from a broad spectrum of applications. A node collaboration scheme is then introduced to further enhance the system performance. We demonstrate through analysis and simulation that, in our hybrid design, a small set of mobile sensors can effectively address the uneven distribution of the static sensors and significantly improve the coverage quality.