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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 --- n/a

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The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond.

Technology: general issues --- History of engineering & technology --- Energy industries & utilities --- hierarchical edge computing --- WSN --- rapid response strategy --- edge node --- fog access points --- cache memory --- convolutional neural network --- proactive caching --- fog computing --- Internet of Things --- service placement --- fog service orchestration --- spectral classification --- portable optical fiber spectrometers --- dew computing --- edge computing --- smartphone --- job scheduling --- scheduling heuristics --- mobile edge computing --- mobile edge server placement --- multiagent RL --- edge security --- offloading computation --- distributed collaboration --- data processing --- dynamic offloading --- IoT --- gateways --- Internet of Things (IoT) --- failure recovery --- FP-Growth algorithm --- association rules --- frequency pattern analysis --- computational offloading --- orchestration --- functional programming --- n/a

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond.

hierarchical edge computing --- WSN --- rapid response strategy --- edge node --- fog access points --- cache memory --- convolutional neural network --- proactive caching --- fog computing --- Internet of Things --- service placement --- fog service orchestration --- spectral classification --- portable optical fiber spectrometers --- dew computing --- edge computing --- smartphone --- job scheduling --- scheduling heuristics --- mobile edge computing --- mobile edge server placement --- multiagent RL --- edge security --- offloading computation --- distributed collaboration --- data processing --- dynamic offloading --- IoT --- gateways --- Internet of Things (IoT) --- failure recovery --- FP-Growth algorithm --- association rules --- frequency pattern analysis --- computational offloading --- orchestration --- functional programming --- n/a