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.

/pdf/internet-of-things-for-smart-cities-u3qvvujxy2.pdf

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

The first major contribution of the IoT Architectural Reference Model (IoT ARM) is the IoT Reference Model itself. Besides models, the IoT Reference Model provides the concepts and definitions on which IoT architectures can be built. This Chapter introduces the IoT Reference Model as a precondition for working with the Reference Architecture that is introduced in Chap. 8.

IoT Reference Model

Reliable network measurements are a fundamental component of networking research as they enable network analysis, system debugging, performance evaluation and optimization. In particular, decoding the LTE control channel would give access to the full base station traffic at a 1 ms granularity, thus allowing for traffic profiling and accurate measurements. Although a few open-source implementations of LTE are available, they do not provide tools to reliably decoding the LTE control channel and, thus, accessing the scheduling information. In this paper, we present OWL, an Online Watcher for LTE that is able to decode all the resource blocks in more than 99% of the system frames, significantly outperforming existing non-commercial prior decoders. Compared to previous attempts, OWL grounds the decoding procedure on information obtained from the LTE random access mechanism. This makes it possible to run our software on inexpensive hardware coupled with almost any software defined radio capable of sampling the LTE signal with sufficient accuracy.

OWL: a reliable online watcher for LTE control channel measurements

Internet of Things Architecture - IoT-A

In this paper we propose a stochastic model to predict user throughput in mobile networks. In particular, the model accounts for uncertainty such as random phenomena (e.g., fast fading) or inexact information (e.g., user location) to derive the statistical distribution of the user throughput. Such a model is highly useful for aiding scheduling and resource allocation decisions. In addition, we provide a taxonomy of prediction techniques to investigate error sources and the main characteristics of prediction accuracy. Finally, we show the versatility of the model by analyzing LTE user throughput for the case where knowledge of either the user's actual position or the congestion level in the cell is inexact.

A Model for Throughput Prediction for Mobile Users

After the burst of the dot-com bubble in the Fall of 2001, the Internet has become a participative medium, which allows users to interact with one another and with the services from anywhere and at any time. The potential of such a change is still to be fully exploited, and phenomena such as social networks and cloud computing are just two of the many innovative solutions that have been born from the Web 2.0. At the same time, a new class of users is establishing itself in the Internet landscape: in fact, with the advent of the Internet of Things (IoT), smart objects are becoming the new, and possibly the biggest, Internet community. In this paper, we propose WebIoT, a novel web application framework, based on Google Web Toolkit, aimed at enhancing the interaction among things and between humans and things. Our framework leverages on the following principles: thing-centric design, modularity and web service communications. We will describe the main components of the framework, their interactions and how simple it is to develop any custom IoT application integrating any number and type of smart things. In particular, we will show how different things can be integrated in the framework, how they interact and how users can exploit these interactions to develop any complex functionality. Finally, we describe a typical HealthCare application for the IoT realized using WebIoT.

Nicola Bui

Papers

IoT Reference Model

OWL: a reliable online watcher for LTE control channel measurements

Internet of Things Architecture - IoT-A

A Model for Throughput Prediction for Mobile Users

WebIoT: A web application framework for the internet of things