Collaborative Scheduling in Highly Dynamic Environments Using Error Inference
Energy constraint is a critical hurdle hindering the practical deployment of long-term wireless sensor network applications. Turning off (i.e., duty cycling) sensors could reduce energy consumption, however at the cost of low sensing fidelity due to sensing gaps introduced. Existing techniques have studied how to collaboratively reduce the sensing gap in space and time, however none of them provides a rigorous approach to confine sensing error within desirable bounds. In this paper, the authors propose a collaborative scheme called CIES, based on the novel concept of error inference between collaborative sensor pairs. Within a node, they use a sensing probability bound to control tolerable sensing error.