Advanced Computing Techniques for Optimization in Cloud
eBook - ePub

Advanced Computing Techniques for Optimization in Cloud

  1. 262 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Advanced Computing Techniques for Optimization in Cloud

About this book

This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.

  • Focuses on virtual machine placement and migration techniques for cloud data centers
  • Presents the role of machine learning and metaheuristic approaches for optimisation in cloud computing services
  • Includes application of placement techniques for quality of service, performance, and reliability improvement
  • Explores data center resource management, load balancing and orchestration using machine learning techniques
  • Analyses dynamic and scalable resource scheduling with a focus on resource management

The text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.

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Yes, you can access Advanced Computing Techniques for Optimization in Cloud by H S Madhusudhan,Punit Gupta,Pradeep Singh Rawat in PDF and/or ePUB format, as well as other popular books in Computer Science & Client-Server Computing. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-Title
  3. Series
  4. Title
  5. Copyright
  6. Contents
  7. Preface
  8. Acknowledgments
  9. Editors
  10. Contributors
  11. Chapter 1 Introduction to Next-Generation Optimization in Cloud Computing Services
  12. Chapter 2 Challenges and Open Issues in Cloud Computing Services
  13. Chapter 3 Resource Management in Cloud Using Nature-Inspired Algorithms
  14. Chapter 4 Machine Learning Approaches for Effective Energy-Efficient Resource Management Strategies in Cloud Services
  15. Chapter 5 Efficient Virtual Machine Allocation Technique Based on Hybrid Approach
  16. Chapter 6 Optimizing Resource Allocation in the Cloud Using Deep Learning
  17. Chapter 7 Reliable Resource Optimization Model for Cloud Using Adversarial Neural Network
  18. Chapter 8 Efficient Migration Technique for Load Balancing in Cloud
  19. Chapter 9 Cost Optimization Model for Cloud Using Machine Learning and Artificial Intelligence
  20. Chapter 10 Scalable Optimization Algorithm for Cloud Resource Scaling
  21. Chapter 11 Fault-Aware Optimization Using Machine Learning and Artificial Intelligence
  22. Chapter 12 Tools and Open Source Platforms for Cloud Computing
  23. Index