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Top1. Introduction
Industries in the energy, environmental, logistics, and surveillance fields have widely employed remote monitoring. Remote monitoring can be associated with Internet of Things (IoT) when the measurements are transmitted over Internet Protocol (IP) networks or the public Internet. A variety of short-range wireless links and/or public mobile networks can be used to connect sensors to data collection servers (Ahmed et al., 2013).
Current smart grid systems and test-beds such as the ones described by Hahn (2013) use data communications and IP networks to facilitate the remote monitoring, analysis, and control of the power grid, with the goal of improving its efficiency and reliability. For instance, as described in Hertzog (2011), “the typical mid-sized utility in the USA has between 2000 to 5000 devices online to provide Supervisory Control and Data Acquisition SCADA communications, condition-based monitoring, and polling for event-specific data in their substations.”
Devices such as smart meters are part of the Distribution/Customer domain. They are connected to the smart grid either by direct connections to the data collection center, or through one or more concentrators or relay agents. In the latter approach, each neighborhood may have one or more concentrators, as shown in Figure 1. Smart meters can be connected to the concentrator using proprietary wireless mesh technologies or access protocols such as IEEE 802.15.4g and 6LoWPAN. It forms a neighborhood area network (NAN). In the research by Berthier et al. (2014), a NAN consisting of 30,000 smart meters and 90 concentrators was studied using real-world packet traces. While the smart meters-to-concentrator links used proprietary communication protocols, the concentrator relays the information to the data collection server using public mobile networks (i.e., cellular links).
Figure 1. A neighborhood area network (NAN) of smart meters using the concentrator approach. A concentrator relays information to and from a data collection server at the Distribution System Operator (DSO)
On the other hand, the direct connections approach uses public mobile networks to connect smart meters directly to the data collection server, as shown in Figure 2. An overview of machine-type-communications or machine-to-machine (M2M) in public mobile networks is described by Norp & Landais (2012). It lists the main requirements to trigger a connection, for instance, from a collection service located in another network trying to reach a device inside the mobile network. Essential requirements are the identity of the device and the application, a sequence number that can be used to detect duplicate packets and send acknowledgments, and other optional requirements. In particular, Cellular IoT (CIoT) offers new possibilities to connect thousands of IoT devices such as sensors and smart meters using cellular networks. The third generation partnership project (3GPP) technical report TR45.820 (2015) proposes new physical and data link layer protocols for CIoT called clean-state radio access technologies. These solutions are being designed for devices that periodically send reports to a data collection agent or management facility. The goals of clean-slate radio are to support low-bandwidth (less than 45 kbps), low-cost devices (less than five dollars), long-battery life (at least 10 years), and extended coverage (i.e., to support larger cells and indoor devices).
Figure 2. A neighborhood area network (NAN) of smart meters using the direct connections approach. Smart meters connect directly to the data collection server through cellular links