Traffic models for machine-to-machine (M2M) communications: types and applications

Machine-to-machine (M2M) or Machine-type Communication (MTC) is expected to have a significant traffic share in future wireless networks. It exhibits considerably different traffic patterns than human-type communication and, thus, requires new traffic models and simulation scenarios. Such models should (i) accurately capture the behaviour of a single MTC device as well as (ii) enable the concurrent simulation of massive numbers of devices (e.g., up to 30 000 devices per cell) with their potential synchronous reactions to an event. In general, source traffic models (i.e., each device is modelled as an autonomous entity) provide higher precision and flexibility. However, their complexity grows quadratically with the number of devices. Aggregated traffic models, on the contrary, are far less precise but their complexity is mainly independent of the number of devices.

In this chapter, we present several modelling strategies, namely, (i) aggregated traffic, (ii) source traffic, and (iii) a hybrid approach. The three models are explained and compared through a common use-case. It allows both to illustrate the trade-off between accuracy and complexity and to guarantee the comparability of future studies by the deployment of common models.