Channel-Awareness and Dependability in Industrial Internet of Things

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.