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Optimized Cloud Resource Management and Scheduling

Book Description

Optimized Cloud Resource Management and Scheduling identifies research directions and technologies that will facilitate efficient management and scheduling of computing resources in cloud data centers supporting scientific, industrial, business, and consumer applications. It serves as a valuable reference for systems architects, practitioners, developers, researchers and graduate level students.



  • Explains how to optimally model and schedule computing resources in cloud computing
  • Provides in depth quality analysis of different load-balance and energy-efficient scheduling algorithms for cloud data centers and Hadoop clusters
  • Introduces real-world applications, including business, scientific and related case studies
  • Discusses different cloud platforms with real test-bed and simulation tools

Table of Contents

  1. Cover image
  2. Title page
  3. Copyright
  4. Foreword
  5. Preface
  6. About the Authors
  7. Acknowledgments
  8. 1. An Introduction to Cloud Computing
    1. Main Contents of this Chapter
    2. 1.1 The background of Cloud computing
    3. 1.2 Cloud computing is an integration of other advanced technologies
    4. 1.3 The driving forces of Cloud computing
    5. 1.4 The development status and trends of Cloud computing
    6. 1.5 The classification of Cloud computing applications
    7. 1.6 The different roles in the Cloud computing industry chain
    8. 1.7 The main features and technical challenges of Cloud computing
    9. Summary
    10. References
  9. 2. Big Data Technologies and Cloud Computing
    1. Main Contents of this Chapter
    2. 2.1 The background and definition of big data
    3. 2.2 Big data problems
    4. 2.3 The dialectical relationship between Cloud computing and big data
    5. 2.4 Big data technologies
    6. Summary
    7. Acknowledgments
    8. References
  10. 3. Resource Modeling and Definitions for Cloud Data Centers
    1. Main Contents of this Chapter
    2. 3.1 Resource models in Cloud data centers
    3. 3.2 Data center resources
    4. 3.3 Categories of Cloud data center resources
    5. 3.4 Constraints and dependencies among resources
    6. 3.5 Data modeling of resources in a Cloud data center
    7. 3.6 Conclusion
    8. Appendix 1: The UML Relationship of Resources
    9. References
  11. 4. Cloud Resource Scheduling Strategies
    1. Main Contents of this Chapter
    2. 4.1 Key technologies of resource scheduling
    3. 4.2 Comparative analysis of scheduling strategies
    4. 4.3 Classification of main scheduling strategies
    5. 4.4 Some constraints of scheduling strategies
    6. 4.5 Scheduling task execution time and trigger conditions
    7. Summary
    8. Appendix: Some elementary terms
    9. References
  12. 5. Load Balance Scheduling for Cloud Data Centers
    1. Main Contents of this Chapter
    2. 5.1 Introduction
    3. 5.2 Related work
    4. 5.3 Problem formulation and description
    5. 5.4 OLRSA algorithm
    6. 5.5 LIF algorithm
    7. 5.6 Discussion and conclusion
    8. References
  13. 6. Energy-efficient Allocation of Real-time Virtual Machines in Cloud Data Centers Using Interval-packing Techniques
    1. Main Contents of this Chapter
    2. 6.1 Introduction
    3. 6.2 GreenCloud architecture
    4. 6.3 Energy-efficient real-time scheduling
    5. 6.4 Performance evaluation
    6. 6.5 Related work
    7. 6.6 Conclusions
    8. References
  14. 7. Energy Efficiency by Minimizing Total Busy Time of Offline Parallel Scheduling in Cloud Computing
    1. Main Contents of this Chapter:
    2. 7.1 Introduction
    3. 7.2 Approximation algorithm and its approximation ratio bound
    4. 7.3 Application to energy efficiency in Cloud computing
    5. 7.4 Performance evaluation
    6. 7.5 Conclusions
    7. References
  15. 8. Comparative Study of Energy-efficient Scheduling in Cloud Data Centers
    1. Main Contents of this Chapter:
    2. 8.1 Introduction
    3. 8.2 Related research
    4. 8.3 Comparative study of offline scheduling algorithms
    5. 8.4 Online algorithms
    6. 8.5 Summary
    7. References
  16. 9. Energy Efficiency Scheduling in Hadoop
    1. Main Contents of this Chapter:
    2. 9.1 Overview
    3. 9.2 Scheduling algorithms
    4. 9.3 Energy control
    5. 9.4 Energy-efficient scheduling for multiple users
    6. 9.5 Performance evaluation
    7. 9.6 Summary
    8. Questions
    9. References
  17. 10. Maximizing Total Weights in Virtual Machines Allocation
    1. Main Contents of this Chapter
    2. 10.1 Introduction
    3. 10.2 Problem formulation: WISWCS
    4. 10.3 WISWCS
    5. 10.4 An exact SAWISWCS
    6. 10.5 Applications of WISWCS
    7. 10.6 Related work
    8. 10.7 Conclusions
    9. References
  18. 11. A Toolkit for Modeling and Simulation of Real-time Virtual Machine Allocation in a Cloud Data Center
    1. Main Contents of this Chapter
    2. 11.1 Introduction of the cloud data center
    3. 11.2 The architecture and main features of CloudSched
    4. 11.3 Performance metrics for different scheduling algorithms
    5. 11.4 Design and implementation of CloudSched
    6. 11.5 Performance evaluation
    7. 11.6 Conclusions
    8. References
  19. 12. Toward Running Scientific Workflows in the Cloud
    1. Main Contents of this Chapter
    2. 12.1 Introduction
    3. 12.2 Related work
    4. 12.3 Integration
    5. 12.4 Experiment
    6. 12.5 Experiment on Amazon EC2
    7. 12.6 Conclusions
    8. References