Edge/Fog Computing Technologies for IoT Infrastructure
Yoo, Seong-eun
Edge/Fog Computing Technologies for IoT Infrastructure - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (231 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-1455-0 9783036514567 9783036514550
10.3390/books978-3-0365-1455-0 doi
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
Edge/Fog Computing Technologies for IoT Infrastructure - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (231 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-1455-0 9783036514567 9783036514550
10.3390/books978-3-0365-1455-0 doi
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