Energy-aware medium access control for energy-harvesting machine-to-machine networks

Abstract

Energy-harvesting is being actively researched for the Machine-to-Machine networks. Without replacement of battery, energy-harvesting enables nodes (or machines) to perform their work permanently by recharging energy store periodically from an external source. After performing given tasks, in many applications, each energy-harvesting node transmits data to the gateway node. Here, the difference in harvested/consumed energy could lead to suboptimal communication due to depletion of energy. In this paper, we design an energy-aware medium access control scheme for energy-harvesting machine-to-machine networks. The proposed algorithm controls delivery error rate due to energy depletion through limited contention among energy-exhausting nodes, and maximize slot efficiency to minimize overall communication duration. Maximizing slot efficiency is implemented in two ways: utility-based and learning-based. Simulation studies have shown that the proposed schemes effectively minimize delivery error rate and communication period, outperforming the existing strategies in the literature.