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.
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2018R1C1B4A01022931) and the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2018-2018-0-01431) supervised by the IITP (Institute for Information & communications Technology Promotion).