An Energy-Efficient Scheduling Algorithm for Real-Time Machine-to-Machine (M2M) Data Reporting

Machine-to-Machine (M2M) or machine-type communication technology standardized by ETSI/3GPP has recently gained a great deal of attention, and has been utilized in a variety of M2M applications, which commonly require real-time data reporting. This paper investigates the energy minimized scheduling problem for real-time reporting of data-critical M2M applications. Although many uplink scheduling algorithms have been proposed for different wireless mobile networks, they are mainly designed for human-to-human communication paradigms. This paper proves this energy minimized scheduling problem is NP-hard, and proposes a heuristic energy-efficient algorithm to address it. Our algorithm effectively schedules the transmissions of an M2M node in the same time slots, so that the active time of the M2M node can be minimized. The experiment results show that under limited bandwidth resource, our algorithm can maintain fairness and low data dropping ratios while achieving energy efficiency for a reasonable number of M2M nodes.