Energy-Efficient Algorithms and Systems in Computing: Optimizing Performance and Sustainability Through Advanced Computational Methods

Energy-Efficient Algorithms and Systems in Computing: Optimizing Performance and Sustainability Through Advanced Computational Methods book cover

Energy-Efficient Algorithms and Systems in Computing: Optimizing Performance and Sustainability Through Advanced Computational Methods

Author(s): Hicham Gibet Tani (Editor), Mohamed Kouissi (Editor), Mohamed Ben Ahmed (Editor), Boudhir Anouar Abdelhakim (Editor), Lotfi Elaachak (Editor)

  • Publisher: Springer
  • Publication Date: October 27, 2025
  • Language: English
  • Print length: 277 pages
  • ISBN-10: 3032041139
  • ISBN-13: 9783032041135

Book Description

This book delivers cutting-edge research focused on reducing energy consumption across computing systems while maintaining performance and scalability. It presents novel methods and architectures that advance the field of sustainable and green technologies. Contributions span topics such as low-power algorithms, green cloud infrastructures, energy-aware IoT systems, and intelligent optimization techniques. Selected from the best papers of SCGT’2025, each chapter offers deep technical insights and practical applications. Aimed at researchers, engineers, and system designers, this book is a valuable resource for building environmentally sustainable computing infrastructures.

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From the Back Cover

This book delivers cutting-edge research focused on reducing energy consumption across computing systems while maintaining performance and scalability. It presents novel methods and architectures that advance the field of sustainable and green technologies. Contributions span topics such as low-power algorithms, green cloud infrastructures, energy-aware IoT systems, and intelligent optimization techniques. Selected from the best papers of SCGT’2025, each chapter offers deep technical insights and practical applications. Aimed at researchers, engineers, and system designers, this book is a valuable resource for building environmentally sustainable computing infrastructures.

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