Understanding the Linguistic Characteristics of Network Signaling for the 'Internet of Things' Using n-Grams

Abstract

In the expanding 'Internet of Things' (IoT), 'Machine-to-Machine' (M2M) applications exist with large homogeneous populations of devices that utilize general-purpose communications infrastructures, and in particular, cellular wireless networks. Understanding the behavior of these applications at large scale can be challenging since they often operate within an environment with various layers of abstraction and where system activity at one layer may lead to unanticipated consequences at other layers. This paper investigates several commercial M2M applications at the cellular wireless "signaling layer," and looks specifically at how the linguistic characteristics, in the form of n-grams, of device interactions with cellular carrier network elements help provide insights into the systems' behavior.