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.