Robust Processor Allocation for Independent Tasks When Dollar Cost for Processors is a Constraint
Sugavanam, P.
Siegel, H.J.
Maciejewski, A.A.
Junxing Zhang
Shestak, M.
Raskey, M.
Pippin, A.
Pichel, R.
Oltikar, M.
Mehta, A.
Panho Lee
Krishnamurthy, Y.
Horiuchi, A.
Guru, K.
Aydin, M.
Al-Otaibi, M.
Ali, S.
Dept. of Electr. & Comput. Eng., Colorado State Univ.;
This paper appears in: Cluster Computing, 2005. IEEE International
Publication Date: Sept. 2005
On page(s): 1-10
Location: Burlington, MA,
ISSN: 1552-5244
ISBN: 0-7803-9486-0
INSPEC Accession Number: 9388143
Digital Object Identifier: 10.1109/CLUSTR.2005.347023
Current Version Published: 2007-04-16
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In a distributed heterogeneous computing system, the resources have different capabilities and tasks have different requirements. Different classes of machines used in such systems typically vary in dollar cost based on their computing efficiencies. Makespan (defined as the completion time for an entire set of tasks) is often the performance feature that is optimized. Resource allocation is often done based on estimates of the computation time of each task on each class of machines. Hence, it is important that makespan be robust against errors in computation time estimates. The dollar cost to purchase the machines for use can be a constraint such that only a subset of the machines available can be purchased. The goal of this study is to: (1) select a subset of all the machines available so that the cost constraint for the machines is satisfied, and (2) find a static mapping of tasks so that the robustness of the desired system feature, makespan, is maximized against the errors in task execution time estimates. Six heuristic techniques to this problem are presented and evaluated
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