Channel-Awareness and Dependability in Industrial Internet of Things
Description
This book provides a systematic treatment of channel-awareness and dependability in the Industrial Internet of Things (IIoT). It also covers the foundations of IIoT, industrial application scenarios, wireless channel characteristics, channel-state awareness, delay optimization, predictive modeling, and security mechanisms. Attention is given to harsh industrial propagation environments, including multipath fading, shadowing, impulse noise, interference, dense deployment, and moving obstacles. This book explains how these channel conditions affect packet delay, reliability, sensing accuracy, prediction quality, and secure communication.
This book develops a cross-layer perspective in which wireless channels are treated not only as sources of uncertainty, but also as measurable and exploitable system variables. It discusses channel-aware access control, latency-tail suppression, hidden-state inference, hybrid physics-AI modeling, online traffic prediction, and prediction-based dependable transmission. It examines security and reliability mechanisms, including channel-based threat analysis, Sybil attack detection, robust physical-layer feature extraction, and multi-kernel detection methods.
The book is intended for graduate students, researchers, and engineers working in wireless communications as well as IIoT, cyber-physical systems, industrial automation, dependable networking, and wireless security. It provides a unified framework for designing reliable, timely, adaptive, and secure IIoT systems under realistic industrial channel conditions.
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Persons
Qihao Li received the Ph.D. degree from the University of Oslo, Norway, in 2019. He was a post-doctoral fellow with the Department of Electrical and Computer Engineering, University of Waterloo, from 2019 to 2021; and a lecturer with the School of Electrical Engineering and Intelligentization, Dongguan University of Technology, from 2022 to 2023. Since 2023, he has been an associate professor with Jilin University, China. His current research focuses on the Industrial IoT, digital twin, and intelligent agent networking and communication. He received the IEEE/CIC ICCC 2024 Best Paper Award and the IEEE ICCT 2025 Young Scholar Award. He served as the Workshop TPC Chair for IEEE VTC 2025, IEEE Globecom 2024, IEEE Infocom 2024, IEEE CIC/ICCC 2023-2024; and a TPC member for several conferences. He served as an associate editor for IEEE Internet of Things Journal and a guest editor for Future Internet Journal .
Qiang Ye received the Ph.D. degree in electrical and computer engineering from the University of Waterloo, ON, Canada, in 2016. Since September 2023, he has been an assistant professor with the Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary (UCalgary), AB, Canada. Before joining UCalgary, he was an assistant professor with the Memorial University of Newfoundland, NL, Canada, from 2021 to 2023, and Minnesota State University, Mankato, USA, from 2019 to 2021. He was with the Department of Electrical and Computer Engineering, University of Waterloo, as a post-doctoral fellow and then a research associate (2016-2019). He has published around 80 research papers in top-ranked journals and conference proceedings. He received the Best Paper Award in the IEEE ICCC in 2024 and the IEEE TCCN Exemplary Editor Award in 2023. He also received the Early Career Research Excellence Award from the Schulich School of Engineering, University of Calgary, in 2024. He serves as an associate editor for prestigious IEEE journals, such as IEEE Internet of Things Journal , IEEE Transactions on Vehicular Technology , IEEE Transactions on Cognitive Communications and Networking , and IEEE Open Journal of the Communications Society .
Kuan Zhang received the B.S. and M.S. degrees in communication engineering and computer applied technology from Northeastern University, China, in 2009 and 2011, respectively, and the Ph.D. degree in electrical and computer engineering from the University of Waterloo, Canada, in 2016. He was a post-doctoral fellow with the University of Waterloo from 2016 to 2017. He is currently an associate professor with the Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, USA. He has published over 50 papers in journals and conferences. His research interests include cybersecurity, big data, and cloud/edge computing. He was a recipient of the Best Paper Award in IEEE WCNC 2013 and SECURECOMM 2016.
Michael Cheffena received the M.Sc. degree in electronics and computer technology from the University of Oslo, Oslo, Norway, in 2005, and the Ph.D. degree from the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, in 2008. In 2007, he was a visiting researcher with Communications Research Centre, Ottawa, ON, Canada. From 2009 to 2010, he conducted a post-doctoral study with University Graduate Center, Kjeller, Norway, and the French Space Agency, Toulouse, France. He is currently a full professor with NTNU, Gjøvik, Norway. His research interests include modeling and prediction of propagation radio channels, signal processing, medium access control, protocol design, antenna sensors, and sensor systems.
Fengye Hu received the B.S. degree from the Department of Precision Instrument, Xi'an University of Technology, China, in 1996, and the M.S. and Ph.D. degrees in communication and information systems from Jilin University, China, in 2000 and 2007, respectively. He served as a visiting scholar of electrical and electronic engineering at Nanyang Technological University (NTU), Singapore, in 2011. He is currently a full professor with the College of Communication Engineering, Jilin University. His current research interests include wireless body area networks, wireless energy and information transfer, energy harvesting, cognitive radio, and space-time communication. He is an editor of IEEE Transactions on Vehicular Technology , IEEE Internet of Things Journal , and China Communications ; and served as an editor for IET Communications .
Content
Chapter 1. Introduction.- Chapter 2. Wireless Channel Analysis and Awareness.- Chapter 3. Channel-Aware Delay Optimization Techniques.- Chapter 4. Predictive Modelling-Enabled End-to-End Transmission Dependability.- Chapter 5. Security and Reliability.- Chapter 6. Conclusions and FutureWorks.