Edge/Fog Computing Technologies for IoT Infrastructure

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 c...

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Bibliographic Details
Format: eBook
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
5G
LWC
n/a
web
Online Access:Open Access: DOAB: description of the publication
Open Access: DOAB, download the publication
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720 1 |a Yoo, Seong-eun  |4 edt 
720 1 |a Kim, Taehong  |4 edt 
720 1 |a Kim, Taehong  |4 oth 
720 1 |a Kim, Youngsoo  |4 edt 
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245 0 0 |a Edge/Fog Computing Technologies for IoT Infrastructure 
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520 |a 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. 
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653 |a 5G 
653 |a algorithm classification 
653 |a cloud computing 
653 |a computational offloading 
653 |a computing 
653 |a container orchestration 
653 |a containers 
653 |a crowding distance 
653 |a custom metrics 
653 |a data manager 
653 |a deep reinforcement learning (DRL) 
653 |a Docker 
653 |a dynamic offloading threshold 
653 |a edge computing 
653 |a evaluation framework 
653 |a evolutionary genetics 
653 |a fast implementation 
653 |a fog computing 
653 |a fog/edge computing 
653 |a fuzzy logic 
653 |a GDPR 
653 |a Horizontal Pod Autoscaling (HPA) 
653 |a hyper-angle 
653 |a Internet of things 
653 |a Internet of Things (IoT) 
653 |a IoT actor 
653 |a Kubernetes 
653 |a leader election 
653 |a load balancing 
653 |a LWC 
653 |a markov decision process (MDP) 
653 |a maximizing throughputs 
653 |a minimizing delay 
653 |a minimizing energy consumption 
653 |a multi-access edge computing 
653 |a multi-objective optimization 
653 |a n/a 
653 |a OpenCL 
653 |a orchestrator 
653 |a Prometheus 
653 |a resource management 
653 |a resource metrics 
653 |a service offloading 
653 |a service placement 
653 |a service provisioning 
653 |a stateful 
653 |a task allocation 
653 |a task offloading 
653 |a task scheduling 
653 |a web 
653 |a Web Assembly 
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