Electrical and Electronic Engineering - Theses
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ItemEnergy consumption of Internet of Things applications and services( 2018)The Internet of Things (IoT) is a new paradigm of interconnectivity that has recently garnered attention in the field of ICT, with an estimated proliferation of 50-200 billion connected devices (i.e. IoT/smart devices) by the end of the decade. This exponential device growth raises concerns as it elicits potential risks including an increase in global energy consumption arising from the deployment of such numbers of devices, the additional network energy cost for handling potential IP traffic increment and the potential impact on the global energy consumption and carbon footprint of the ICT industry. However, due to the development/deployment of many IoT services being in their embryonic stage, there is little research on the characterisation of energy consumption of these services in the literature. In this thesis, we aim to investigate and gain a better understanding of the energy consumption of IoT network applications and services. We do so by developing energy consumption models and in turn, energy-efficient network architectures for the delivery of IoT services. To achieve this goal, we employ and model a few case studies including two of the most well-known and widely deployed IoT services, home automation and security (HAS) and video surveillance services. For the assessment of energy consumption of an IoT service, we obtained a range of IoT products including a consumer-off-the-shelf (COTS) HAS system, as a representative example. We analyse and model (through direct measurements) the energy consumption of each component and the complete system including an IoT attributable share of the home gateway energy consumption. Our results reveal that the energy consumption of a simple COTS IoT service is non-trivial (more than one-third) when compared to the annual energy usage of a mid-size suburban home. HAS energy consumption globally becomes substantial, in comparison with the ICT industry’s energy consumption projections, when IoT service numbers are scaled using published deployment estimates. The IoT leverages a number of existing and emerging technologies to provide a complete end-to-end service, one of which is short-range wireless network protocols. We obtained, measured and analysed the energy-efficiency of five of the most popular COTS wireless protocol modules, Bluetooth Classic & Low Energy, ZigBee, Wi-Fi and RF 433 MHz. We compare these technologies through their application in a simple domestic stock-control IoT service with three communication paradigm options. The results demonstrate that careful consideration should be given to the choice of a communication mode and wireless interface in IoT application development. Such a decision should be driven by the volume of traffic exchange and the frequency of transmission of the application/service. The emergence of edge/fog computing as an alternative to cloud computing promises to tackle some critical pitfalls of cloud including energy consumption. To investigate the energy efficiency of IoT network architectures, the data-intensive video surveillance IoT service is employed as a case study. Using the end-to-end energy models developed, we investigate four (Local, Edge and Cloud) dissimilar network architectures for the delivery of IoT services. We show that it is more energy-wise to adopt an edge-based architecture for on-demand streaming applications but both live streaming and computationally-intensive applications are more energy-efficient when designed with a local access architecture. We further study a number of access network technologies for the IoT. They include very-high-bit-rate digital subscriber line (VDSL2), passive optical network (PON), point-to-point optical network (PtP), fourth generation long term evolution (4G LTE), low-power wide area networks (LPWA) and Wi-Fi access (Shared and Unshared). We show that for low data access rates, LPWA is more energy-efficient while Shared Wi-Fi access with PON backhaul is most energy-efficient for medium to higher data access rates. The findings in this thesis reinforce the need for careful design consideration when developing future IoT solutions.