Temporal QOS Management in Scientific Cloud Workflow Systems

Temporal QOS Management in Scientific Cloud Workflow Systems

by Xiao Liu, Jinjun Chen, Yun Yang
Released February 2012
Publisher(s): Elsevier
ISBN: 9780123972958

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Book description

Cloud computing can provide virtually unlimited scalable high performance computing resources. Cloud workflows often underlie many large scale data/computation intensive e-science applications such as earthquake modelling, weather forecasting and astrophysics. During application modelling, these sophisticated processes are redesigned as cloud workflows, and at runtime, the models are executed by employing the supercomputing and data sharing ability of the underlying cloud computing infrastructures.

Temporal QOS Management in Scientific Cloud Workflow Systems focuses on real world scientific applications which often must be completed by satisfying a set of temporal constraints such as milestones and deadlines. Meanwhile, activity duration, as a measurement of system performance, often needs to be monitored and controlled. This book demonstrates how to guarantee on-time completion of most, if not all, workflow applications. Offering a comprehensive framework to support the lifecycle of time-constrained workflow applications, this book will enhance the overall performance and usability of scientific cloud workflow systems.



  • Explains how to reduce the cost to detect and handle temporal violations while delivering high quality of service (QoS)
  • Offers new concepts, innovative strategies and algorithms to support large-scale sophisticated applications in the cloud
  • Improves the overall performance and usability of cloud workflow systems

Table of contents

  1. Cover Image
  2. Content
  3. Title
  4. Copyright
  5. Preface
  6. Acknowledgements
  7. About the Authors
  8. 1. Introduction
    1. 1.1 Temporal QoS in Scientific Cloud Workflow Systems
    2. 1.2 Motivating Example and Problem Analysis
    3. 1.3 Key Issues of This Research
    4. 1.4 Overview of This Book
  9. 2. Literature Review and Problem Analysis
    1. 2.1 Workflow Temporal QoS
    2. 2.2 Temporal Consistency Model
    3. 2.3 Temporal Constraint Setting
    4. 2.4 Temporal Consistency Monitoring
    5. 2.5 Temporal Violation Handling
  10. 3. A Scientific Cloud Workflow System
  11. 4. Novel Probabilistic Temporal Framework
    1. 4.1 Framework Overview
    2. 4.2 Component I: Temporal Constraint Setting
    3. 4.3 Component II: Temporal Consistency Monitoring
    4. 4.4 Component III: Temporal Violation Handling
  12. COMPONENT I. Temporal Constraint Setting
    1. 5. Forecasting Scientific Cloud Workflow Activity Duration Intervals
      1. 5.1 Cloud Workflow Activity Durations
      2. 5.2 Related Work and Problem Analysis
      3. 5.3 Statistical Time-Series-Pattern-Based Forecasting Strategy
      4. 5.4 Evaluation
    2. 6. Temporal Constraint Setting
      1. 6.1 Related Work and Problem Analysis
      2. 6.2 Probability-based Temporal Consistency Model
      3. 6.3 Setting Temporal Constraints
      4. 6.4 Case Study
  13. COMPONENT II. Temporal Consistency Monitoring
    1. 7. Temporal Checkpoint Selection and Temporal Verification
      1. 7.1 Related Work and Problem Analysis
      2. 7.2 Temporal Checkpoint Selection and Verification Strategy
      3. 7.3 Evaluation
  14. COMPONENT III. Temporal Violation Handling
    1. 8. Temporal Violation Handling Point Selection
      1. 8.1 Related Work and Problem Analysis
      2. 8.2 Adaptive Temporal Violation Handling Point Selection Strategy
      3. 8.3 Evaluation
    2. 9. Temporal Violation Handling
      1. 9.1 Related Work and Problem Analysis
      2. 9.2 Overview of Temporal Violation Handling Strategies
      3. 9.3 A Novel General Two-Stage Local Workflow Rescheduling Strategy for Recoverable Temporal Violations
      4. 9.4 Three-Level Temporal Violation Handling Strategy
      5. 9.5 Comparison of GA- and ACO-based Workflow Rescheduling Strategies
      6. 9.6 Evaluation of Three-Level Temporal Violation Handling Strategy
    3. 10. Conclusions and Contribution
      1. 10.1 Overall Cost Analysis for Temporal Framework
      2. 10.2 Summary of This Book
      3. 10.3 Contributions of This Book
  15. APPENDIX. Notation Index
  16. Bibliography

Product information

  • Title: Temporal QOS Management in Scientific Cloud Workflow Systems
  • Author(s): Xiao Liu, Jinjun Chen, Yun Yang
  • Release date: February 2012
  • Publisher(s): Elsevier
  • ISBN: 9780123972958