A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

ReSCon '12, Research Student Conference: Book of Abstracts

The fifth SED Research Student Conference (ReSCon2012) was hosted over three days, 18-20 June 2012, in the Hamilton Centre at Brunel University. The conference consisted of 130 oral and 70 poster presentations, based on the high quality and diverse research being conducted within the School of Engineering and Design by postgraduate research students. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected

Smart Urban Water Networks

This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems

On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds

Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified for stimulating the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed

AN EFFICIENT INTERFERENCE AVOIDANCE SCHEME FOR DEVICE-TODEVICE ENABLED FIFTH GENERATION NARROWBAND INTERNET OF THINGS NETWOKS’

Narrowband Internet of Things (NB-IoT) is a low-power wide-area (LPWA) technology built on long-term evolution (LTE) functionalities and standardized by the 3rd-Generation Partnership Project (3GPP). Due to its support for massive machine-type communication (mMTC) and different IoT use cases with rigorous standards in terms of connection, energy efficiency, reachability, reliability, and latency, NB-IoT has attracted the research community. However, as the capacity needs for various IoT use cases expand, the LTE evolved packet core (EPC) system's numerous functionalities may become overburdened and suboptimal. Several research efforts are currently in progress to address these challenges. As a result, an overview of these efforts with a specific focus on the optimized architecture of the LTE EPC functionalities, the 5G architectural design for NB-IoT integration, the enabling technologies necessary for 5G NB-IoT, 5G new radio (NR) coexistence with NB-IoT, and feasible architectural deployment schemes of NB-IoT with cellular networks is discussed. This thesis also presents cloud-assisted relay with backscatter communication as part of a detailed study of the technical performance attributes and channel communication characteristics from the physical (PHY) and medium access control (MAC) layers of the NB-IoT, with a focus on 5G. The numerous drawbacks that come with simulating these systems are explored. The enabling market for NB-IoT, the benefits for a few use cases, and the potential critical challenges associated with their deployment are all highlighted. Fortunately, the cyclic prefix orthogonal frequency division multiplexing (CPOFDM) based waveform by 3GPP NR for improved mobile broadband (eMBB) services does not prohibit the use of other waveforms in other services, such as the NB-IoT service for mMTC. As a result, the coexistence of 5G NR and NB-IoT must be manageably orthogonal (or quasi-orthogonal) to minimize mutual interference that limits the form of freedom in the waveform's overall design. As a result, 5G coexistence with NB-IoT will introduce a new interference challenge, distinct from that of the legacy network, even though the NR's coexistence with NB-IoT is believed to improve network capacity and expand the coverage of the user data rate, as well as improves robust communication through frequency reuse. Interference challenges may make channel estimation difficult for NB-IoT devices, limiting the user performance and spectral efficiency. Various existing interference mitigation solutions either add to the network's overhead, computational complexity and delay or are hampered by low data rate and coverage. These algorithms are unsuitable for an NB-IoT network owing to the low-complexity nature. As a result, a D2D communication based interference-control technique becomes an effective strategy for addressing this problem. This thesis used D2D communication to decrease the network bottleneck in dense 5G NBIoT networks prone to interference. For D2D-enabled 5G NB-IoT systems, the thesis presents an interference-avoidance resource allocation that considers the less favourable cell edge NUEs. To simplify the algorithm's computing complexity and reduce interference power, the system divides the optimization problem into three sub-problems. First, in an orthogonal deployment technique using channel state information (CSI), the channel gain factor is leveraged by selecting a probable reuse channel with higher QoS control. Second, a bisection search approach is used to find the best power control that maximizes the network sum rate, and third, the Hungarian algorithm is used to build a maximum bipartite matching strategy to choose the optimal pairing pattern between the sets of NUEs and the D2D pairs. The proposed approach improves the D2D sum rate and overall network SINR of the 5G NB-IoT system, according to the numerical data. The maximum power constraint of the D2D pair, D2D's location, Pico-base station (PBS) cell radius, number of potential reuse channels, and cluster distance impact the D2D pair's performance. The simulation results achieve 28.35%, 31.33%, and 39% SINR performance higher than the ARSAD, DCORA, and RRA algorithms when the number of NUEs is twice the number of D2D pairs, and 2.52%, 14.80%, and 39.89% SINR performance higher than the ARSAD, RRA, and DCORA when the number of NUEs and D2D pairs are equal. As a result, a D2D sum rate increase of 9.23%, 11.26%, and 13.92% higher than the ARSAD, DCORA, and RRA when the NUE’s number is twice the number of D2D pairs, and a D2D’s sum rate increase of 1.18%, 4.64% and 15.93% higher than the ARSAD, RRA and DCORA respectively, with an equal number of NUEs and D2D pairs is achieved. The results demonstrate the efficacy of the proposed scheme. The thesis also addressed the problem where the cell-edge NUE's QoS is critical to challenges such as long-distance transmission, delays, low bandwidth utilization, and high system overhead that affect 5G NB-IoT network performance. In this case, most cell-edge NUEs boost their transmit power to maximize network throughput. Integrating cooperating D2D relaying technique into 5G NB-IoT heterogeneous network (HetNet) uplink spectrum sharing increases the system's spectral efficiency and interference power, further degrading the network. Using a max-max SINR (Max-SINR) approach, this thesis proposed an interference-aware D2D relaying strategy for 5G NB-IoT QoS improvement for a cell-edge NUE to achieve optimum system performance. The Lagrangian-dual technique is used to optimize the transmit power of the cell-edge NUE to the relay based on the average interference power constraint, while the relay to the NB-IoT base station (NBS) employs a fixed transmit power. To choose an optimal D2D relay node, the channel-to-interference plus noise ratio (CINR) of all available D2D relays is used to maximize the minimum cell-edge NUE's data rate while ensuring the cellular NUEs' QoS requirements are satisfied. Best harmonic mean, best-worst, half-duplex relay selection, and a D2D communication scheme were among the other relaying selection strategies studied. The simulation results reveal that the Max-SINR selection scheme outperforms all other selection schemes due to the high channel gain between the two communication devices except for the D2D communication scheme. The proposed algorithm achieves 21.27% SINR performance, which is nearly identical to the half-duplex scheme, but outperforms the best-worst and harmonic selection techniques by 81.27% and 40.29%, respectively. As a result, as the number of D2D relays increases, the capacity increases by 14.10% and 47.19%, respectively, over harmonic and half-duplex techniques. Finally, the thesis presents future research works on interference control in addition with the open research directions on PHY and MAC properties and a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis presented in Chapter 2 to encourage further study on 5G NB-IoT

Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as enhanced Mobile Broadband (eMBB), massive Machine Type Communications (mMTC) and Ultra-Reliable and Low Latency Communications (URLLC), the mMTC brings the unique technical challenge of supporting a huge number of MTC devices in cellular networks, which is the main focus of this paper. The related challenges include Quality of Service (QoS) provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and Narrowband IoT (NB-IoT). Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenario along with the recent advances towards enhancing its learning performance and convergence. Finally, we discuss some open research challenges and promising future research directions

New Waves of IoT Technologies Research – Transcending Intelligence and Senses at the Edge to Create Multi Experience Environments

The next wave of Internet of Things (IoT) and Industrial Internet of Things (IIoT) brings new technological developments that incorporate radical advances in Artificial Intelligence (AI), edge computing processing, new sensing capabilities, more security protection and autonomous functions accelerating progress towards the ability for IoT systems to self-develop, self-maintain and self-optimise. The emergence of hyper autonomous IoT applications with enhanced sensing, distributed intelligence, edge processing and connectivity, combined with human augmentation, has the potential to power the transformation and optimisation of industrial sectors and to change the innovation landscape. This chapter is reviewing the most recent advances in the next wave of the IoT by looking not only at the technology enabling the IoT but also at the platforms and smart data aspects that will bring intelligence, sustainability, dependability, autonomy, and will support human-centric solutions.acceptedVersio

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

Convergence of millimeter-wave and photonic interconnect systems for very-high-throughput digital communication applications

In the past, radio-frequency signals were commonly used for low-speed wireless electronic systems, and optical signals were used for multi-gigabit wired communication systems. However, as the emergence of new millimeter-wave technology introduces multi-gigabit transmission over a wireless radio-frequency channel, the borderline between radio-frequency and optical systems becomes blurred. As a result, there come ample opportunities to design and develop next-generation broadband systems to combine the advantages of these two technologies to overcome inherent limitations of various broadband end-to-end interconnect systems in signal generation, recovery, synchronization, and so on. For the transmission distances of a few centimeters to thousands of kilometers, the convergence of radio-frequency electronics and optics to build radio-over-fiber systems ushers in a new era of research for the upcoming very-high-throughput broadband services. Radio-over-fiber systems are believed to be the most promising solution to the backhaul transmission of the millimeter-wave wireless access networks, especially for the license-free, very-high-throughput 60-GHz band. Adopting radio-over-fiber systems in access or in-building networks can greatly extend the 60-GHz signal reach by using ultra-low loss optical fibers. However, such high frequency is difficult to generate in a straightforward way. In this dissertation, the novel techniques of homodyne and heterodyne optical-carrier suppressions for radio-over-fiber systems are investigated and various system architectures are designed to overcome these limitations of 60-GHz wireless access networks, bringing the popularization of multi-gigabit wireless networks to become closer to the reality. In addition to the advantages for the access networks, extremely high spectral efficiency, which is the most important parameter for long-haul networks, can be achieved by radio-over-fiber signal generation. As a result, the transmission performance of spectrally efficient radio-over-fiber signaling, including orthogonal frequency division multiplexing and orthogonal wavelength division multiplexing, is broadly and deeply investigated. On the other hand, radio-over-fiber is also used for the frequency synchronization that can resolve the performance limitation of wireless interconnect systems. A novel wireless interconnects assisted by radio-over-fiber subsystems is proposed in this dissertation. In conclusion, multiple advantageous facets of radio-over-fiber systems can be found in various levels of end-to-end interconnect systems. The rapid development of radio-over-fiber systems will quickly change the conventional appearance of modern communications.PhDCommittee Chair: Gee-Kung Chang; Committee Member: Bernard Kippelen; Committee Member: Shyh-Chiang Shen; Committee Member: Thomas K. Gaylord; Committee Member: Umakishore Ramachandra