Temporal QOS Management in Scientific Cloud Workflow Systems

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  • Publisher : Elsevier
  • Release : 23 February 2012
  • ISBN : 9780123970107
  • Page : 155 pages
  • Rating : 4.5/5 from 103 voters

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Chapter 1 Introduction -- Chapter 2 Literature Review and Problem Analysis -- Chapter 3 A Scientific Cloud Workflow System -- Chapter 4 Novel Probabilistic Temporal Framework -- Chapter 5 Forecasting Scientific Cloud Workflow Activity Duration Intervals -- Chapter 6 Temporal Constraint Setting -- Chapter 7 Temporal Checkpoint Selection and Temporal Verification -- Chapter 8 Temporal Violation Handling Point Selection -- Chapter 9 Temporal Violation Handling -- Chapter 10 Conclusions and Contribution Bibliography.

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Temporal QOS Management in Scientific Cloud Workflow Systems

Temporal QOS Management in Scientific Cloud Workflow Systems
  • Author : Xiao Liu,Jinjun Chen,Yun Yang
  • Publisher : Elsevier
  • Release Date : 2012-02-23
  • ISBN : 9780123970107
GET THIS BOOKTemporal QOS Management in Scientific Cloud Workflow Systems

Chapter 1 Introduction -- Chapter 2 Literature Review and Problem Analysis -- Chapter 3 A Scientific Cloud Workflow System -- Chapter 4 Novel Probabilistic Temporal Framework -- Chapter 5 Forecasting Scientific Cloud Workflow Activity Duration Intervals -- Chapter 6 Temporal Constraint Setting -- Chapter 7 Temporal Checkpoint Selection and Temporal Verification -- Chapter 8 Temporal Violation Handling Point Selection -- Chapter 9 Temporal Violation Handling -- Chapter 10 Conclusions and Contribution Bibliography.

Temporal QOS Management in Scientific Cloud Workflow Systems

Temporal QOS Management in Scientific Cloud Workflow Systems
  • Author : Xiao Liu,Jinjun Chen,Yun Yang
  • Publisher : Elsevier
  • Release Date : 2012-02-20
  • ISBN : 9780123972958
GET THIS BOOKTemporal QOS Management in Scientific Cloud Workflow Systems

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

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