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QoS guided Min-Min heuristic for grid task scheduling

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Abstract

Task scheduling is an integrated component of computing. With the emergence of Grid and ubiquitous computing, new challenges appear in task scheduling based on properties such as security, quality of service, and lack of central control within distributed administrative domains. A Grid task scheduling framework must be able to deal with these issues. One of the goals of Grid task scheduling is to achieve high system throughput while matching applications with the available computing resources. This matching of resources in a non-deterministically shared heterogeneous environment leads to concerns over Quality of Service (QoS). In this paper a novel QoS guided task scheduling algorithm for Grid computing is introduced. The proposed novel algorithm is based on a general adaptive scheduling heuristics that includes QoS guidance. The algorithm is evaluated within a simulated Grid environment. The experimental results show that the new QoS guided Min-Min heuristic can lead to significant performance gain for a variety of applications. The approach is compared with others based on the quality of the prediction formulated by inaccurate information.

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Authors and Affiliations

  1. Department of Computer Science, Illinois Institute of Technology, IL, USA

    XiaoShan He & Xianhe Sun

  2. Mathematics and Computer Science Division, Argonne National Laboratory, IL, USA

    Gregor von Laszewski

Authors
  1. XiaoShan He
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  2. Xianhe Sun
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  3. Gregor von Laszewski
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Corresponding author

Correspondence to XiaoShan He.

Additional information

This research was supported in part by the National Science Foundation, of USA under NSF Grant Nos.EIA-0224377, ANI-0123930, EIA-0130673, and by the Army Research Office under ARO Grant No. DAAD19-01-1-0432.

HE XiaoShan is currently a Ph.D. candidate in Illinois Institute of Technology, IL, USA. She received her M.S. degree in computer science from Illinois Institute of Technology in 2002, and her B.S. degree in computer engineering from University of Electronic Science and Technology of China in 1999. Her current research interests are scheduling algorithms in grid computing and pervasive computing.

SUN XianHe received his Ph.D. degree in computer science from Michigan State University in 1990. He was a staff scientist at ICASE, NASA Langley Research Center and was an associate professor in the Computer Science Department at Louisiana State University (LSU). Currently he is a professor and the director of the Scalable Computing Software Laboratory in the Computer Science Department at Illinois Institute of Technology (IIT), and a guest faculty at the Argonne National Laboratory. Dr. Sun's research interests include parallel and distributed processing, software system, performance evaluation, and scientific computing. He has published intensively in the field and his research search has been supported by DoD, DoE, NASA, NSF, and other government agencies. He is a senior member of IEEE, a member of ACM, New York Academy of Sciences, PHI KAPPA PHI, and has served and are serving as the chairman or on the program committee for a number of international conferences and workshops. He received the ONR and ASEE Certificate of Recognition award in 1999, and received the Best Paper Award from the International Conference on Parallel Processing (ICP01) in 2001.

Gregor von Laszewski is a scientist at Argonne National Laboratory and a fellow of the Computation Institute at University of Chicago. He received a Ph.D. degree in 1996 from Syracuse University. He is an expert in Grid computing. His current research interests are in the areas of parallel, distributed, and grid computing. Specifically, he is working on topics in the area of using commodity technologies within grid services, applications, and portals.

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He, X., Sun, X. & von Laszewski, G. QoS guided Min-Min heuristic for grid task scheduling. J. Comput. Sci. & Technol. 18, 442–451 (2003). https://doi.org/10.1007/BF02948918

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  • DOI: https://doi.org/10.1007/BF02948918

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