Energy-Efficient Scheduling Algorithms for Real-Time Data Reporting in 4G LTE Machine-to-Machine Communication Networks

Machine-to-machine (M2M) communications protocols, e.g., Machine Type Communications (MTC) in 3GPP LTE, support a variety of Machine to Machine (M2M) applications, which requires real-time data reporting. Many uplink scheduling algorithms are primarily designed for human-to-human applications rather than for M2M applications. These scheduling algorithms typically are based on the fact that the machines in MTC are battery-powered and aim to reduce the energy consumption. We notice that the current literature considers either the problem of sleep-time maximization or transmission power minimization, but not both. In this paper, we systematically consider all energy consumption factors of M2M real-time reporting. Using MTC in LTE as an example for M2M communications, in this paper, we propose two energy-efficient scheduling algorithms to minimize the total energy consumption of machines for M2M communications. The two proposed algorithms utilize the distance between a machine and the serving eNB (i.e., base station in LTE). Our performance study shows that our algorithms have performance enhancement in terms of energy consumption compared to other algorithms in the previous works. Furthermore, our algorithms can maintain high scheduling success ratio and fairness.