Online stream processing of machine-to-machine communications traffic: A platform comparison

Abstract

In a machine-to-machine (M2M) communications system, the deployed devices relay data from on-board sensors to a back-end application over a wireless network. Since the cellular network provides very good coverage (especially in inhabited areas) and is relatively inexpensive, commercial M2M applications often prefer it to other technologies such as WiFi or satellite links. Unfortunately, having been originally designed with human users in mind, the cellular network provides little support to monitor millions of unattended devices. For this reason, it is extremely important to monitor the underlying signalling traffic to detect misbehaving devices or network problems. In the cellular network used by M2M communications systems, the network elements communicate using the Signalling System #7 (SS7), and a real-life system can generate tens of millions of SS7 messages per hour. This paper reports the results of our practical investigation on the possibility to use distributed stream processing systems (DSPSs) to perform real-time analysis of SS7 traffic in a commercial M2M communications system consisting of hundreds of thousands of devices. Through a thorough experimental evaluation based on the analysis of realworld SS7 traces, we present and compare the implementations of a DSPS-based data analysis application on top of either the well-known Storm DSPS or the Quasit middleware. The results show that, by using DSPS services, we are able to largely meet the real-time processing requirements of our use-case scenario.

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

“…For this investigation, we consider several subsets of the larger population of devices whose communications are captured and made available using [8] and [9]. In particular, we consider the SS7 traffic for the devices of several commercial M2M applications over a one week period as seen in Table I.…”

“…Using methods developed in [8] and [9], we are able to capture the raw network packets exchanged among cellular network elements and convert them into a stream of timestamped subject/predicate pairs that are the essential linguistic components of the SS7 protocol.…”