Intelligent IoT for the Digital World

Incorporating 5G Communications and Fog/Edge Computing Technologies

Yang Yang, Xu Chen, Rui Tan, Yong Xiao

• Publisher: Wiley
• Year: 2021
• Print ISBN: 9781119593546
• eBook ISBN: 9781119593560
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

INTELLIGENT I O T FOR THE DIGITAL WORLD

DISCOVER HOW THE INTELLIGENT INTERNET OF THINGS WILL CHANGE THE INFORMATION AND COMMUNICATION TECHNOLOGY INDUSTRY IN THE NEXT DECADE

In the digital world, most data and Internet of Things (IoT) services need to be efficiently processed and executed by intelligent algorithms using local or regional computing resources, thus greatly saving and reducing communication bandwidth, end-to-end service delay, long-distance data transmissions, and potential privacy breaches. This book proposes a pyramid model, where data, computing and algorithm jointly constitute the triangular base to support a variety of user-centric intelligent IoT services at the spire by using different kinds of smart terminals or devices.

This book provides a state-of-the-art review of intelligent IoT technologies and applications, discusses the key challenges and opportunities facing the digital world, and answers the following five critical questions:

• What is the most feasible network architecture to effectively provide sufficient resources anywhere anytime for intelligent IoT application scenarios?
• How do we efficiently discover, allocate and manage computing, communication and caching resources in heterogeneous networks across multiple domains and operators?
• How do we agilely achieve adaptive service orchestration and reliable service provisioning to meet dynamic user requirements in real time?
• How do we effectively protect data privacy in IoT applications, where IoT devices and edge/fog computing nodes only have limited resources and capabilities?
• How do we continuously guarantee and maintain the synchronization and reliability of wide-area IoT systems and applications?

Written for professionals working in 5G/IoT technology development, service management and big data analytics, this book offers an overview of intelligent IoT service architecture, key technologies, important applications and future technological trends.

1
IoT Technologies and Applications

1.1 Introduction

As a new dimension to the world of information and communication technologies (ICTs), the concept of the internet of things (IoT) aims at providing “connectivity for anything”, “by embedding short‐range mobile transceivers into a wide array of additional gadgets and everyday items, enabling new forms of communication between people and things, and between things themselves”, according to the seventh International Telecommunication Union (ITU) Internet Reports 2005 (International Telecommunication Union (ITU), 2005). In recent years, different IoT technologies and standards have been actively developed for different industrial sectors and application scenarios, such as smart city, intelligent transportation system, safety, and security system, intelligent agriculture, environment monitoring, smart factory, intelligent manufacturing, smart home, and healthcare. Various IoT‐centered business models and value chains have become, consolidated, and popular; these IoT applications are effectively accelerating the digitalization and transformation progresses of traditional industries (Union, 2016). As a result, they have generated tremendous economic and social benefits to our society, as well as huge impacts on people's daily life.

Sensors, machines, and user devices are the “things”, which are usually equipped with limited energy resources and simple sensing, computing, communication, motion, and control capabilities. By using a large number of sensors in the field, a typical IoT system can effectively expand its service coverage and capability in sensing, collecting, and processing different types of raw data obtained from the physical world. Most redundant data with low value will be aggregated or filtered for saving scarce communication resources, i.e. bandwidth, storage,and energy. Selected data with potential values, e.g., characteristics of unexpected events, will be transmitted from different sites through multi‐hop communication networks to a centralized computing facility, such as a data center, for further in‐depth investigation. New information will be extracted, or new events will be discovered, from this more comprehensive analysis of massive data from a much larger area across multiple sites and locations.

In the early days, IoT systems were usually developed according to rigid rules or requirements. The main purpose is to improve the perception of the physical world, as well as the efficiency of data collection and analysis, in different IoT applications such as environment monitoring and emergency management. As a well‐known application‐driven IoT architecture, the ISO/IEC 30141‐IoT Reference Architecture is often adopted in system designs and service deployments (Union, 2016). Data acquisition involves all kinds of sensors, such as RFID, MEMS, bar code, and video camera. However, due to dynamic application scenarios and environments, the key function and challenge for IoT systems are high‐quality data collection (transmission) through wireless ad hoc networks. Many wireless access and networking technologies have been developed for ensuring timely and reliable connectivity and transmission for data collection at low cost and low energy consumption (Yang et al., 2006b,a, Zhao et al., 2015). In addition to the existing standards for mobile communications, the internet, and broadcasting networks, a series of wireless communication technologies have been developed for supporting IoT data transmissions in various application scenarios, e.g. RFID, Wi‐Fi, NFC, ZigBee, LoRa, and Sigfox (Jia et al., 2012, Li et al., 2011, Vedat et al., 2012, Alliance, 2012, Augustin et al., 2016, Sigfox, 2018a). By collaboratively analyzing data from multiple sensors in different areas, a more comprehensive perception of the actual environment and a timely understanding of the exact situation will be achieved, thus enabling better decision making and performance optimization for particular industrial operations.

Nowadays, a series of advanced technologies on smart sensing, pervasive computing, wireless communication, pattern recognition, and behavior analysis have been widely applied and integrated for supporting more and more sophisticated IoT applications, such as intelligent transportation system and intelligent manufacturing. Such complex applications can significantly improve system automation and efficiency in massive data analysis and task execution. To achieve this goal, the key function and challenge for IoT systems is accurate information extraction, which heavily depends on domain‐specific knowledge, valuable experience, and technical know‐how contributed by real experts and field workers. In order to make IoT systems more accessible and deployable, the fourth‐generation (4G) and fifth‐generation (5G) mobile communication standards have specified several important IoT application scenarios, i.e. Narrowband IoT (NB‐IoT) in 4G massive Machine Type Communications (mMTC) and ultra‐reliable and low latency communications (URLLC) in 5G (3GP, 2017, 3GPP, 2016a, Yang et al., 2018). Furthermore, the latest developments in cloud computing and big data technologies enable fast and accurate analysis of huge volumes of structured and non‐structured data, creating lots of business opportunities for the development of more sophisticated and intelligent IoT systems. The continuous progression and widespread deployment of IoT technologies have been transforming many industrial sectors and commercial ecosystems. Now, IoT applications and services are becoming indispensable to our daily lives and business models, e.g., remote control of door locks, lights, and appliances at homes and offices, real‐time modeling of resource consumption patterns and streamline business processes in factories, constant surveillance for property security, public safety and emergency management in cities.

To meet the fast‐growing demands of various IoT applications and services for different businesses and customers, leading ICT companies, such as Amazon, Google, Microsoft, Cisco, Huawei, Alibaba, and JD, have launched their own cloud‐based IoT platforms for data‐centric services. However, these enterprise‐level platforms are not designed for data sharing, nor service collaboration. General concerns of data security and customer privacy strictly prevent the attempts of connecting and integrating them for much bigger commercial benefits and global influences. Besides, it is even harder to overcome the existing barriers of vertical industries and realize cross‐domain information exchanges for minimizing the redundancies and fragments at different but related IoT applications.

In the future, when artificial intelligence (AI) technologies are widely adopted in most industrial sectors and application domains, new links will be established between those domain‐specific island‐like solutions. In most cases, they are not used to share original data, but only to exchange necessary knowledge that is purposely learned from separated/protected datasets for customized applications. To realize this ambitious vision, the key function and challenge for future IoT systems is innovative knowledge creation, which requires high‐quality data, super‐intelligent algorithms, and more computing resources everywhere. Centralized cloud computing alone cannot support this fundamental change, while dispersive fog computing technologies will fill the computational gap along the continuum from cloud to things. Therefore, future intelligent IoT systems will fully utilize the best available computing resources in their neighborhood and in the cloud to calculate novel effective mechanisms and solutions, which are acceptable and executable across different enterprise platforms, industrial sectors, and application domains. In this way, those domain‐specific IoT systems are not closed or isolated any more, they will become much more powerful and influential by working collaboratively, thus significantly saving global resources, improving overall performance, and maximizing potential benefits in all systems. There is no doubt that future IoT applications and services will be shifting from data‐centric to knowledge‐centric. Very soon, they will become better than human‐designed ones, since they are taught by us and powered by accumulated data, sophisticated AI algorithms, endless computing resources, and fast evolution. Eventually, they will help us not only search and identify useful information from massive raw data, but more importantly, discover, and create new knowledge to expand our horizons and capabilities.

The rest of this chapter is organized as follows. Section 1.2 reviews some well‐known and emerging IoT standards and technologies. Section 1.3 introduces intelligent IoT technologies, including an intelligent user‐centered IoT network, in which data, computing power, and intelligent algorithms are distributed around its users. Typical IoT applications are summarized in Section 1.4. New requirements and challenges of IoT systems are analyzed in Section 1.5. Finally, Section 1.6 concludes this chapter.

1.2 Traditional IoT Technologies

1.2.1 Traditional IoT System Architecture

The IoT is a platform where every day devices become smarter, every day processing becomes more intelligent, and every day communication becomes more informative. While the IoT is still seeking its own shape, its effects have already started in making incredible strides as a universal solution media for the connected scenario. Architecture specific study does always pave the conformation of the related field. IoT is a dynamic global network infrastructure with the capability of self‐configuring based on standards and interoperable protocols. IoT enables physical and virtual “things” to use intel...

Table of contents

• Cover
• Table of Contents
• Title Page
• Copyright
• Preface
• Acknowledgments
• Acronyms
• 1 IoT Technologies and Applications
• 2 Computing and Service Architecture for Intelligent IoT
• 3 Cross‐Domain Resource Management Frameworks
• 4 Dynamic Service Provisioning Frameworks
• 5 Lightweight Privacy‐Preserving Learning Schemes
• 6 Clock Synchronization for Wide‐area Applications
• 7 Conclusion
• Index
• End User License Agreement