Traffic modeling for Machine-to-Machine (M2M) last mile wireless access networks

The most challenging issue in Machine-to-Machine (M2M) last mile wireless access networks is the management of a large number of M2M devices that generate a vast amount of M2M traffic. The communications traffic for various M2M applications or services is classified as Fixed-Scheduling (FS) or Event-Driven (ED). The FS traffic is an operational traffic, which occurs on a periodic basis, such as reports on the measured data, sent by M2M sensor devices. The ED traffic, which is assumed to have a higher priority, is triggered by occurrence of specific events, such as the traffic generated by M2M devices, due to failure in the monitored systems. To date, we have not seen any traffic model for M2M last mile wireless access networks, which incorporates the different characteristics of ED and FS traffic. Thus, in this paper, we develop an analytical traffic model for M2M last mile wireless access networks based on a priority queuing system, which considers the combination of both periodic FS and random ED traffic. By using the proposed model, we derive expressions for the mean queuing delay and blocking probability of each traffic class. The derived analytical expressions are validated by simulations of a wireless network model and are shown to agree very well.