Energy-efficient routing in mobile wireless sensor networks using mobility prediction

Abstract

A method is presented for efficiently and reliably routing data packets from a static information source to a mobile sink through a multi-hop wireless sensor network. While the source and all sensor nodes are located at fixed and known positions, the mobile sink estimates and tracks its location, speed, and acceleration with a Kalman filter. To reliably and timely route data packets, the source predicts the location of the mobile sink. The prediction is updated by receiving messages from the mobile sink, containing its current location, speed, and acceleration. These messages are sent only if the Euclidean norm of the error between the predicted state and the state estimated by the Kalman filter exceeds a pre-defined threshold. The control messages and the data packets are forwarded in a multi-hop fashion through the network using geographic routing. Simulation results demonstrate that the proposed scheme outperforms conventional routing protocols in terms of packet transfer reliability, latency, and energy efficiency.