Energy efficient sleep scheduling based on moving directions in target tracking sensor network

Abstract

This paper presents a target direction-based sleep scheduling algorithm (TDSS) for target tracking surveillance sensor networks. TDSS reduces the number of the proactively awakened sensor nodes and schedules their sleep pattern to enhance energy efficiency but suffer little performance loss. Both approaches are based on two probabilistic distribution models of target moving directions, normal distribution and linear distribution. We compare TDSS with the two models against the legacy circle-based proactively waking up scheme (Circle) and a working node reducing algorithm - MCTA. The evaluation result shows that TDSS achieves better energy efficiency but with less performance loss in terms of detection probability and detection delay.