Title page for etd-0723108-124114


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URN etd-0723108-124114
Author Shih-Yung Li
Author's Email Address No Public.
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Department Information Management
Year 2007
Semester 2
Degree Master
Type of Document
Language English
Title A Probability-based Framework for Dynamic Resource Scheduling in Data-Intensive Grid Environment
Date of Defense 2008-06-23
Page Count 56
Keyword
  • Grid
  • Probability
  • Resource Allocation
  • Workflow
  • Abstract Recent enthusiasm in grid computing has resulted in a tremendous amount of research in resource scheduling techniques for tasks in a (scientific) workflow. There are many factors that may affect the scheduling results, one of which is whether the application is computing-intensive or data-intensive. Most of the grid scheduling researches focus on a single aspect of the environments. In this thesis, we base on our previous work, a probability-based framework for dynamic resource scheduling, and consider data transmission overhead in our scheduling algorithms. The goal is to dynamically assign resources to tasks so as to maximize the probability of completing the entire workflow within a desired total response time. We propose two algorithms for the dynamic resource scheduling in grid environment, namely largest deadline completion probability (LDCP) and smallest deadline completion probability (SDCP). Furthermore, considering the data transmission overhead, we propose a suite of push-based scheduling algorithms, which schedule all the immediate descendant tasks when a task is completed. These are algorithms will be compared to the pull-demand scheduling algorithms in our previous work and workflow-based algorithms proposed by other researchers. We use GridSim toolkit to model the grid environment and evaluate the performance of the various scheduling algorithms.
    Advisory Committee
  • Te-Min Chang - chair
  • Wan-Shiou Yang - co-chair
  • San-Yih Hwang - advisor
  • Files
  • etd-0723108-124114.pdf
  • indicate in-campus access in a year and off_campus not accessible
    Date of Submission 2008-07-23

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