Energy-efficient scheduling with delay constraints for wireless sensor networks: A calculus-based perspective

This paper focuses on developing a calculus framework which provides guidelines for designing energy-efficient scheduling algorithm in wireless sensor networks (WSNs). By exploiting the unique characteristics of fixed sampling period and data delivery deadline constraints in WSNs, we transform the energy-efficient data scheduling problem with individual packet delay constraints to an energy-efficient service curve construction problem. We then address the problem by introducing a local optimality theorem and based on which, two efficient scheduling algorithms are proposed. Our approaches dynamically divide the whole network lifetime into the scheduling cycles according to the backlogged data and the delay constraints, leading to significantly more energy gain over the traditional scheduling schemes. We further conduct extensive simulations to evaluate the effectiveness of our algorithms.