doi: 10.4304//jsw.4.10.1102-1109
Research on Tasks Scheduling Algorithms for Dynamic and Uncertain Computing Grid Based on a+bi Connection Number of SPA
2College of Computing Sciences, New Jersey Institute of Technology, Newark, New Jersey, USA
3Institute of Zhuji connection mathematics. Zhuji,China
Abstract—Task scheduling algorithms are key techniques in task management system of computing grid. Because of the uncertainty nature of a grid, traditional task scheduling algorithms do not work well in an open, heterogeneous and dynamic grid environment of real world. In this paper, Set Pair Analysis (SPA), a new soft computation method is used to process the synthetic uncertainty in the task scheduling of a computing grid. After introducing SPA and its application, the paper goes on to introduce the definition of connection number to express the uncertain Expected Time to Compute of tasks, analysis operation properties and linear order relation suitable for computing grid scheduling. Three online uncertain dynamic scheduling algorithms, OUD_OLB, OUD_MET, OUD_MCT, and three batch uncertain dynamic scheduling algorithms BUD_Min-min, BUD_Min-max, BUD_Surferage, are presented for the uncertain dynamic computing grid. Theoretical analysis and experimental results illustrate that these algorithms are capable of representing the dynamics and uncertainty in a computing grid environment. These algorithms are the generalization of traditional grid scheduling algorithms, and they possess high value in theory and application in a grid environment. Certainly it will be a new method to design tasks scheduling algorithm in uncertain computing grid environment.
Index Terms—computing grid; Dynamic;uncertainty; task scheduling; algorithm
Cite: HUANG Decai, YUAN Yuan, ZHANG Li-jun, ZHAO Ke-qin, "Research on Tasks Scheduling Algorithms for Dynamic and Uncertain Computing Grid Based on a+bi Connection Number of SPA," Journal of Software vol. 4, no. 10, pp. 1102-1109, 2009.
General Information
ISSN: 1796-217X (Online)
Abbreviated Title: J. Softw.
Frequency: Quarterly
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
Abstracting/ Indexing: DBLP, EBSCO,
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