Green Edge/Fog/Cloud Computing in Intelligent Applications across Industries

Submission Deadline: 23 May 2022 (closed)

Guest Editors

Dr. Bala Murugan, Albert Einstein Engineering and Research Labs, India.
Dr. BalaAnand Muthu, Adhiyamaan College of Engineering, India.
Dr. Sheng-Lung Peng, National Taipei university of business, Taiwan.
Dr. Mohd Helmy Abd Wahab, Universiti Tun Hussein Onn Malaysia, Malaysia.


Industrial automation has substantially altered the way machines and people interact in the modern period, owing to the tremendous rise of information flows and almost infinite computer capacity Nearly every advanced manufacturing segment may benefit from intelligent automation technologies, and massive computer power enables the development of the next generation of software and hardware automatons capable of perceptual and cognitive activities. Currently, the notion of green edge/fog/cloud computing has had an enormous impact on the research community, as it allows optimized cloud resource utilization with reduced energy usage in a cloud infrastructure without sacrificing the quality of service. Due to improved communication infrastructures, edge and fog computing are becoming more widely accessible and efficient host storage and computational capabilities in the cloud and on edge devices. Green computing technology is concerned with the construction, production, leveraging, and configuration of the server and peripheral devices such as storage devices, screens, copy machines, and heterogeneous wireless devices efficiently and effectively while not harming the environment.


The adaptability of edge/fog/cloud computing framework enables users to choose whether to perform Artificial Intelligence (AI) tasks such as decision making on sensor data at the edge or in fog and cloud infrastructures. Furthermore, machine learning (ML) training and data analysis have sophisticated computation competencies but are located further away from actuators and in-place real-time applications. Hence novel edge/fog/cloud computing architectures, as a result, can offer the type of assistance that Internet of Things applications need to deploy artificial intelligence approaches in an effective and scalable manner. Besides, for sustainable ecological, green edge/fog/cloud computing is driven by economic considerations since the information technology sector's electricity demand and energy costs are alarming. Furthermore, green edge/fog/cloud computing uses a variety of approaches, such as green network infrastructure, hybridization, energy computational efficiency, and grid computing, to decrease energy consumption and environmental waste while maintaining high-performance levels. However, integrating and using green computing continues to be problematic in Intelligent Applications across Industries. Many critical technologies are required, such as energy-efficient infrastructure configurations at the system virtualization and virtualization levels. The requirement for Intelligent Applications across Industries is increasing, and so are the research difficulties in the green edge/fog/cloud computing era. Hence this special issue focuses on Green Edge/Fog/Cloud Computing in Intelligent Applications across Industries.


The topics of interest for the special issue include, but not limited to the following:

Emerging challenges and trends in green edge/fog/cloud computing for Intelligent Applications across Industries

AI-enabled edge computing for decentralized Intelligent Applications across Industries

Integration and migration towards edge/fog computing for Industrial 4.0

Trust, privacy and security for intelligent green edge/fog/cloud computing

Enhanced intelligent decision-making and energy-efficient resource scheduling algorithm for green computing

Advanced environmentally approachable green computing for Industrial 4.0 and beyond

Proactive energy consumption supervision and monitoring in traditional cloud framework

Green Computing based Energy-efficient power management for industrial applications

Challenges and opportunities toward eco-friendly green cloud computing technology

Convergence of Blockchain with distributed edges for efficient green edge/fog/cloud computing


Green Computing; cloud computing; Blockchain; Edge computing; Fog computing

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