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Wireless sensor networks are penetrating our daily lives, and they are starting to be deployed even in an industrial environment. The research on such industrial wireless sensor networks (IWSNs) considers more stringent requirements of robustness, reliability, and timeliness in each network layer. This Special Issue presents the recent research result on industrial wireless sensor networks. Each paper in this Special Issue has unique contributions in the advancements of industrial wireless sensor network research and we expect each paper to promote the relevant research and the deployment of IWSNs.

History of engineering & technology --- (m,k)-firm model --- adaptive real-time routing --- traffic management --- industrial wireless multimedia sensor network --- WLAN --- MAC --- full duplex --- spatial group --- OFDMA --- IEEE 802.11be --- energy-efficiency --- industrial wireless sensor networks --- reference node selection --- time synchronization --- disaster --- hazards --- cluster-tree --- remote sensing --- industrial wireless sensor network --- distributed scheduling --- weight factor --- ad-hoc network --- fairness --- ISA 100.11a --- wireless networked control systems --- link stability --- protocols for Industrial Wireless Sensor Networks (IWSN) --- IWSN standards --- IEEE 802.15.4 --- WirelessHART --- ISA100.11a --- real-time communications in IWSN --- Wireless Networked Control Systems (WNCSs) --- IWSN testbeds and applications

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Wireless sensor networks are penetrating our daily lives, and they are starting to be deployed even in an industrial environment. The research on such industrial wireless sensor networks (IWSNs) considers more stringent requirements of robustness, reliability, and timeliness in each network layer. This Special Issue presents the recent research result on industrial wireless sensor networks. Each paper in this Special Issue has unique contributions in the advancements of industrial wireless sensor network research and we expect each paper to promote the relevant research and the deployment of IWSNs.

History of engineering & technology --- (m,k)-firm model --- adaptive real-time routing --- traffic management --- industrial wireless multimedia sensor network --- WLAN --- MAC --- full duplex --- spatial group --- OFDMA --- IEEE 802.11be --- energy-efficiency --- industrial wireless sensor networks --- reference node selection --- time synchronization --- disaster --- hazards --- cluster-tree --- remote sensing --- industrial wireless sensor network --- distributed scheduling --- weight factor --- ad-hoc network --- fairness --- ISA 100.11a --- wireless networked control systems --- link stability --- protocols for Industrial Wireless Sensor Networks (IWSN) --- IWSN standards --- IEEE 802.15.4 --- WirelessHART --- ISA100.11a --- real-time communications in IWSN --- Wireless Networked Control Systems (WNCSs) --- IWSN testbeds and applications --- (m,k)-firm model --- adaptive real-time routing --- traffic management --- industrial wireless multimedia sensor network --- WLAN --- MAC --- full duplex --- spatial group --- OFDMA --- IEEE 802.11be --- energy-efficiency --- industrial wireless sensor networks --- reference node selection --- time synchronization --- disaster --- hazards --- cluster-tree --- remote sensing --- industrial wireless sensor network --- distributed scheduling --- weight factor --- ad-hoc network --- fairness --- ISA 100.11a --- wireless networked control systems --- link stability --- protocols for Industrial Wireless Sensor Networks (IWSN) --- IWSN standards --- IEEE 802.15.4 --- WirelessHART --- ISA100.11a --- real-time communications in IWSN --- Wireless Networked Control Systems (WNCSs) --- IWSN testbeds and applications

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The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices. Moreover, emerging IoT applications, such as augmented and virtual reality (AR/VR), intelligent transportation systems, and smart factories require ultra-low latency for data communication and processing. Fog/edge computing is a new computing paradigm where fully distributed fog/edge nodes located nearby end devices provide computing resources. By analyzing, filtering, and processing at local fog/edge resources instead of transferring tremendous data to the centralized cloud servers, fog/edge computing can reduce the processing delay and network traffic significantly. With these advantages, fog/edge computing is expected to be one of the key enabling technologies for building the IoT infrastructure. Aiming to explore the recent research and development on fog/edge computing technologies for building an IoT infrastructure, this book collected 10 articles. The selected articles cover diverse topics such as resource management, service provisioning, task offloading and scheduling, container orchestration, and security on edge/fog computing infrastructure, which can help to grasp recent trends, as well as state-of-the-art algorithms of fog/edge computing technologies.

Information technology industries --- cloud computing --- container orchestration --- custom metrics --- Docker --- edge computing --- Horizontal Pod Autoscaling (HPA) --- Kubernetes --- Prometheus --- resource metrics --- fog computing --- task allocation --- multi-objective optimization --- evolutionary genetics --- hyper-angle --- crowding distance --- containers --- leader election --- load balancing --- stateful --- multi-access edge computing --- orchestrator --- task offloading --- fuzzy logic --- 5G --- fog/edge computing --- service provisioning --- service placement --- service offloading --- Internet of Things (IoT) --- task scheduling --- markov decision process (MDP) --- deep reinforcement learning (DRL) --- resource management --- algorithm classification --- evaluation framework --- web --- Web Assembly --- OpenCL --- LWC --- fast implementation --- Internet of things --- IoT actor --- data manager --- GDPR --- computing --- computational offloading --- dynamic offloading threshold --- minimizing delay --- minimizing energy consumption --- maximizing throughputs --- cloud computing --- container orchestration --- custom metrics --- Docker --- edge computing --- Horizontal Pod Autoscaling (HPA) --- Kubernetes --- Prometheus --- resource metrics --- fog computing --- task allocation --- multi-objective optimization --- evolutionary genetics --- hyper-angle --- crowding distance --- containers --- leader election --- load balancing --- stateful --- multi-access edge computing --- orchestrator --- task offloading --- fuzzy logic --- 5G --- fog/edge computing --- service provisioning --- service placement --- service offloading --- Internet of Things (IoT) --- task scheduling --- markov decision process (MDP) --- deep reinforcement learning (DRL) --- resource management --- algorithm classification --- evaluation framework --- web --- Web Assembly --- OpenCL --- LWC --- fast implementation --- Internet of things --- IoT actor --- data manager --- GDPR --- computing --- computational offloading --- dynamic offloading threshold --- minimizing delay --- minimizing energy consumption --- maximizing throughputs