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Temporal QOS management in scientific cloud workflow systems

著者: Xiao Liu; Jinjun Chen; Yun Yang
出版商: Waltham, MA : Elsevier, 2012.
丛书: Elsevier insights.
版本/格式:   电子图书 : 文献 : 英语查看所有的版本和格式
数据库:WorldCat
提要:
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  再读一些...
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详细书目

类型/形式: Electronic books
附加的形体格式: Print version:
(OCoLC)ocn761843513
材料类型: 文献, 互联网资源
文件类型: 互联网资源, 计算机文档
所有的著者/提供者: Xiao Liu; Jinjun Chen; Yun Yang
ISBN: 9780123970107 0123970105 9780123972958 0123972957
OCLC号码: 778786621
描述: 1 online resource (xiv, 140 p.)
内容: 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.
丛书名: Elsevier insights.
责任: Xiao Liu, Jinjun Chen, Yun Yang.

摘要:

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.

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