https://minerva-access.unimelb.edu.au/bitstream/handle/11343/197439/1207.0203v1.pdf

Internet of Things (IoT): A vision, architectural elements, and future directions

This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper starts by providing a horizontal overview of the IoT. Then, we give an overview of some technical details that pertain to the IoT enabling technologies, protocols, and applications. Compared to other survey papers in the field, our objective is to provide a more thorough summary of the most relevant protocols and application issues to enable researchers and application developers to get up to speed quickly on how the different protocols fit together to deliver desired functionalities without having to go through RFCs and the standards specifications. We also provide an overview of some of the key IoT challenges presented in the recent literature and provide a summary of related research work. Moreover, we explore the relation between the IoT and other emerging technologies including big data analytics and cloud and fog computing. We also present the need for better horizontal integration among IoT services. Finally, we present detailed service use-cases to illustrate how the different protocols presented in the paper fit together to deliver desired IoT services.

Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications

The Internet of Things (IoT) shall be able to incorporate transparently and seamlessly a large number of different and heterogeneous end systems, while providing open access to selected subsets of data for the development of a plethora of digital services. Building a general architecture for the IoT is hence a very complex task, mainly because of the extremely large variety of devices, link layer technologies, and services that may be involved in such a system. In this paper, we focus specifically to an urban IoT system that, while still being quite a broad category, are characterized by their specific application domain. Urban IoTs, in fact, are designed to support the Smart City vision, which aims at exploiting the most advanced communication technologies to support added-value services for the administration of the city and for the citizens. This paper hence provides a comprehensive survey of the enabling technologies, protocols, and architecture for an urban IoT. Furthermore, the paper will present and discuss the technical solutions and best-practice guidelines adopted in the Padova Smart City project, a proof-of-concept deployment of an IoT island in the city of Padova, Italy, performed in collaboration with the city municipality.

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Internet of Things for Smart Cities

In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this article, we survey the literature till 2011 on the enabling technologies for the Smart Grid. We explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system. We also propose possible future directions in each system. colorred{Specifically, for the smart infrastructure system, we explore the smart energy subsystem, the smart information subsystem, and the smart communication subsystem.} For the smart management system, we explore various management objectives, such as improving energy efficiency, profiling demand, maximizing utility, reducing cost, and controlling emission. We also explore various management methods to achieve these objectives. For the smart protection system, we explore various failure protection mechanisms which improve the reliability of the Smart Grid, and explore the security and privacy issues in the Smart Grid.

/pdf/smart-grid-the-new-and-improved-power-grid-a-survey-4jypbbgv3j.pdf

Smart Grid — The New and Improved Power Grid: A Survey

Mobile network operators are expected to face significant traffic increase in the upcoming years. One alternative method is to intelligently move transmissions to times of network underutilization, either on 3G/4G or by offloading to WiFi. Video content, predicted by Cisco to constitute 69% of mobile traffic, offers the greatest potential for offloading. To this end, the demonstrated app strives to relieve the mobile network in a two ways. First, long-term prefetching of promising videos based on posts from the user's Online Social Network feed is performed. The knowledge about which video is likely being requested in the near future offers the opportunity to schedule the transmission according to its probability of being watched. Second, the approach is complemented with short-term prefetching, which is used whenever a content could not be downloaded by long-term prefetching. In this case, resources are optimized so as to maximize the communication efficiency while preserving the quality of service. The demonstrated app considers the smartphone's observed cellular network history to optimize the mobile throughput. A customized video player implements both the long-term and short-term prefetching. It reduces both the load on mobile networks, decreases playback pausing events and hereby achieves a high QoE. Thus, the player addresses both the operators' and the users' needs.

Media download optimization through prefetching and resource allocation in mobile networks

In this letter we discuss the exploitation of aggregated mobility patterns in mobile networks including heterogeneous multiple access techniques. We advocate the use of knowledge about neighboring devices to create routing groups (RGs) of adjacent nodes in order to optimize radio resource management. Basically, RGs consist of aggregated logical structures which are built and maintained at the application layer. Their use allows decreased signaling overhead between groups of nodes and access points (AP) and, at the same time, improved connectivity, which is achieved through the exploitation of technology diversity and relaying schemes. We illustrate a simple yet effective analytical model, and validate it through accurate simulation results. Finally, we show the effectiveness of the RG approach in terms of resource efficiency, throughput and multiple access performance.

/pdf/improved-resource-management-through-user-aggregation-in-42616p8uh3.pdf

Improved Resource Management through User Aggregation in Heterogeneous Multiple Access Wireless Networks

In this paper we present McMAC, a lightweight, low power and multi-channel MAC protocol for duty cycled Wireless Sensor Networks (WSNs) based on the strobed preamble sampling technique first presented in XMAC. Although many MAC protocols for duty cycled WSNs have been proposed so far, McMAC is the first protocol, to the best of the authors' knowledge, that exploits in a lightweight fashion parallel transmissions over the entire range of IEEE 802.15.4 channels. This results in considerable improvements in terms of energy saving and achievable throughput with respect to preamble sampling based protocols relying on a single channel. McMAC has been implemented in the ns-3 simulation environment, on top of the IEEE 802.15.4 module, which we have improved in order to better account for multi channel support and dynamic spectrum representation. Finally, ns-3 has been used to validate and test McMAC comparing its performance against that of XMAC.

McMAC: a power efficient, short preamble multi-channel medium access control protocol for wireless sensor networks

Energy efficiency and self sustainability are among the primary objectives for networks of embedded devices, such as those of sensor networks and Internet of Things. In this paper we present a reference framework to obtain the optimal configuration parameters of networked devices with energy scavenging capabilities. Specifically, we derive an optimization method that links a simple and yet effective energy consumption model to network topology configurations and to the average energy that is harvested from the environment. This model is efficiently solved using interior point algorithms, making it possible to obtain optimal communication parameters and their feasibility regions, so as to ensure the perpetual operation of embedded communicating devices. Moreover, our framework allows for a dynamic system configuration as a function of the harvested energy income rate, thus making the considered networks flexible and self-adaptable.

Nicola Bui

Papers

Media download optimization through prefetching and resource allocation in mobile networks

Improved Resource Management through User Aggregation in Heterogeneous Multiple Access Wireless Networks

McMAC: a power efficient, short preamble multi-channel medium access control protocol for wireless sensor networks

Dimensioning self-sufficient networks of energy harvesting embedded devices

Fine-grained LTE radio link estimation for mobile phones