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Edge/Fog Computing Technologies for IoT Infrastructure
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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.
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Keywords
- 5G
- algorithm classification
- Cloud computing
- computational offloading
- computing
- container orchestration
- Containers
- crowding distance
- custom metrics
- data manager
- deep reinforcement learning (DRL)
- docker
- dynamic offloading threshold
- Economics, finance, business & management
- edge computing
- evaluation framework
- Evolutionary genetics
- fast implementation
- fog computing
- fog/edge computing
- Fuzzy logic
- GDPR
- Horizontal Pod Autoscaling (HPA)
- hyper-angle
- Industry & industrial studies
- Information technology industries
- Internet of Things
- Internet of Things (IoT)
- IoT actor
- Kubernetes
- leader election
- load balancing
- LWC
- Markov decision process (MDP)
- maximizing throughputs
- Media, information & communication industries
- minimizing delay
- minimizing energy consumption
- multi-access edge computing
- multi-objective optimization
- n/a
- OpenCL
- orchestrator
- Prometheus
- Resource Management
- resource metrics
- service offloading
- service placement
- service provisioning
- stateful
- task allocation
- task offloading
- task scheduling
- Web
- Web Assembly
Links
DOI: 10.3390/books978-3-0365-1455-0Editions