Active Sensing and Its Application to Sensor Node Reconfiguration

Abstract

This paper presents a perturbation/correlation-based active sensing method and its application to sensor node configuration for environment monitoring. Sensor networks are widely used as data measurement tools, especially in dangerous environments. For large scale environment monitoring, a large number of nodes is required. For optimal measurements, the placement of nodes is very important. Nonlinear spring force-based configuration is introduced. Perturbation/correlation-based estimation of the gradient is developed and it is much more robust because it does not require any differentiation. An algorithm for tuning the stiffness using the estimated gradient for node reconfiguration is presented. The performance of the proposed algorithm is discussed with simulation results.