Mobile Anchor Assisted Error Bounded Sensing in Sensor Networks: An Implementation Perspective

Energy constraint is a critical hurdle hindering the practical deployment of long-term wireless sensor network applications. Turning off (that is, duty cycling) sensors could reduce energy consumption, however, this would occur at the cost of low sensing fidelity due to sensing gaps introduced. Existing techniques focus mainly on scheduling a network with static anchors. Few methods provides a rigorous approach to confining sensing errors within desirable bounds while seeking to optimize the tradeoff between energy consumption and accuracy of predictions. In this work, we propose a sensing scheduling scheme, called MAS, to support mobile anchors in sensor networks. Within a node, we use a sensing probability bound to control tolerable sensing errors. While communicating with the mobile anchor, nodes trigger additional sensing activities to accommodate the QoS requirement in mobile communication. We validated the concept by constructing a lab-grade mobile anchor that fully supports 4G-LTE communications for monitoring applications. We further conducted simulations to investigate system performance. The simulation results demonstrated that the MAS achieved enhancement performance compared to several other sensing schemes.