Energy Efficient Algorithms And Green Data Centers For Sustainable Computing

Energy Efficient Algorithms and Green Data Centers for Sustainable Computing

As the demand for computing surges, the need for sustainable solutions has never been more urgent. Energy-efficient algorithms and green data centers are the at the forefront of sustainable computing which aims to reduce carbon footprints while maintaining high- performance capabilities. Traditional data centers consume a vast amount of electricity, contributing to the environmental impact. By integrating energy efficient workloads and renewable energy sources, green data centers can minimize waste and enhance efficiency. These advancements support environmental sustainability while driving cost savings and operational resilience, paving the way for a greener digital future. Energy Efficient Algorithms and Green Data Centers for Sustainable Computing explores sustainable computing, including advancements in energy efficient algorithms and green data center strategies. It addresses the environmental challenges and increasing energy demands of modern computing. This book covers topics such as energy efficient algorithms, green data centers, and sustainability metrics and assessments, and is an excellent resource for researchers, academicians, data scientists, environmental scientists, software developers, and technology entrepreneurs.

Multidisciplinary Approach in Research Area (Volume-12)

Handbook of Whale Optimization Algorithm

Handbook of Whale Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides the most in-depth look at an emerging meta-heuristic that has been widely used in both science and industry. Whale Optimization Algorithm has been cited more than 5000 times in Google Scholar, thus solving optimization problems using this algorithm requires addressing a number of challenges including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters to name a few. This handbook provides readers with in-depth analysis of this algorithm and existing methods in the literature to cope with such challenges. The authors and editors also propose several improvements, variants and hybrids of this algorithm. Several applications are also covered to demonstrate the applicability of methods in this book. - Provides in-depth analysis of equations, mathematical models and mechanisms of the Whale Optimization Algorithm - Proposes different variants of the Whale Optimization Algorithm to solve binary, multiobjective, noisy, dynamic and combinatorial optimization problems - Demonstrates how to design, develop and test different hybrids of Whale Optimization Algorithm - Introduces several application areas of the Whale Optimization Algorithm, focusing on sustainability - Includes source code from applications and algorithms that is available online