Sustainable Cloud and Energy Services: Principles and Practice



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Written by
Wilson Rivera
Published by
Springer
QR code for Sustainable Cloud and Energy Services: Principles and Practice
Published
Oct, 2017
ISBN 10
3319622374
ISBN 13
9783319622378
Pages
268

About Sustainable Cloud and Energy Services: Principles and Practice


This is the first book entirely devoted to providing a perspective on the state-of-the-art of cloud computing and energy services and the impact on designing sustainable systems. Cloud computing services provide an efficient approach for connecting infrastructures and can support sustainability in different ways. For example, the design of more efficient cloud services can contribute in reducing energy consumption and environmental impact. The chapters in this book address conceptual principles and illustrate the latest achievements and development updates concerning sustainable cloud and energy services. This book serves as a useful reference for advanced undergraduate students, graduate students and practitioners interested in the design, implementation and deployment of sustainable cloud based energy services. Professionals in the areas of power engineering, computer science, and environmental science and engineering will find value in the multidisciplinary approach to sustainable cloud and energy services presented in this book.

Table of Contents


Chapter 1 Cloud Computing And Internet Of Things Integration: Architecture, Applications, Issues, And Challenges
Chapter 2 A Self-Governing And Decentralized Network Of Smart Objects To Share Electrical Power Autonomously
Chapter 3 Implementing Energy Service Automation Using Cloud Technologies And Public Communications Networks
Chapter 4 Privacy-Preserving Smart Grid Tariff Decisions With Blockchain-Based Smart Contracts
Chapter 5 Energy Cloud: Services For Smart Buildings
Chapter 6 Dynamic Virtual Machine Consolidation Algorithms For Energy-Efficient Cloud Resource Management: A Review
Chapter 7 Energy Saving In Cloud By Using Enhanced Instance Based Learning (Eibl) For Resource Prediction
Chapter 8 Short-Term Prediction Model To Maximize Renewable Energy Usage In Cloud Data Centers
Chapter 9 Optimal Sizing Of A Micro-Hydrokinetic Pumped-Hydro-Storage Hybrid System For Different Demand Sectors
Chapter 10 Impact Of Different South African Demand Sectors On Grid-Connected Pv Systems' Optimal Energy Dispatch Under Time Of Use Tariff

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