Analysis and modelling of power consumption-aware priority-based scheduling for M2M data aggregation over long-term-evolution networks

The deployment of billions of machine-to-machine (M2M) devices is expected to have an enticing effluence in cellular networks. Data aggregation is an attractive scheme to decrease power consumption; however, it introduces longer delay to the aggregated data. M2M devices have disparate traffic types with different delay requirements. In this study, the author proposes a priority-based data aggregation scheme at the M2M gateway that effectively maintains a good trade-off between the power consumption and delay requirement. An analytical model that considers the idle and busy states behaviour of the aggregator using preemption M/G/1 queuing with priority disciplines is developed and analysed. The performance measures in terms of system delay and power consumption are derived and used to quantify the trade-off between M2M delay sensitive traffic and low power consumption provisions. Based on the numerical and simulation results, the proposed scheme provides a good trade-off between delay and power consumption.