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Computational Intelligence for Green Cloud Computing and Digital Waste Management: Intelligent Computing Resource Management in Cloud/Fog/Edge Distributed Computing

Computational Intelligence for Green Cloud Computing and Digital Waste Management: Intelligent Computing Resource Management in Cloud/Fog/Edge Distributed Computing
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Author(s): Sana Dahmani (Independent Researcher, Germany)
Copyright: 2024
Pages: 25
Source title: Computational Intelligence for Green Cloud Computing and Digital Waste Management
Source Author(s)/Editor(s): K. Dinesh Kumar (Amrita Vishwa Vidyapeetham, India), Vijayakumar Varadarajan (The University of New South Wales, Australia), Nidal Nasser (College of Engineering, Alfaisal University, Saudi Arabia)and Ravi Kumar Poluru (Institute of Aeronautical Engineering, India)
DOI: 10.4018/979-8-3693-1552-1.ch007

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Abstract

Intelligent resource management across fog, edge, and cloud computing entails dynamic allocation, optimal utilization, and robust security measures. Cloud computing adopts a centralized approach to provision resources, whereas edge and fog computing allocate resources at the periphery, strategically minimizing latency. The incorporation of AI/ML algorithms has a pivotal role, enabling resource prediction for anticipating demand, detecting anomalies, and optimizing allocation efficiently. The self-organizing management aspect facilitates autonomous adaptation. Resource virtualization abstracts physical resources into flexible virtual counterparts, complemented by meticulous accounting that tracks consumption and costs. The inclusion of security-aware measures ensures protection against unauthorized access. This comprehensive approach not only enhances performance, scalability, and security but also promotes adaptive scaling and proactive decision-making. Additionally, the implementation of green IT practices optimizes resource utilization, effectively reducing environmental impact.

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