Ali, Syed, authorAl-Otaibi, Mohammad, authorAydin, Mahir, authorGuru, Kumara, authorHoriuchi, Aaron, authorKrishnamurthy, Yogish, authorLee, Panho, authorMehta, Ashish, authorOltikar, Mohana, authorPichel, Ron, authorPippin, Alan, authorRaskey, Michael, authorShestak, Vladimir, authorZhang, Junxing, authorMaciejewski, Anthony A., authorSiegel, H. J., authorSugavanam, Prasanna, authorIEEE, publisher2007-01-032007-01-032006Sugavanam, Prasanna, et al., Robust Processor Allocation for Independent Tasks When Dollar Cost for Processors is a Constraint, [2005 IEEE International Conference on Cluster Computing (CLUSTER): Burlington, MA, 27-30 September, 2005]: 1-10.http://hdl.handle.net/10217/67387In 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.born digitalproceedings (reports)eng©2006 IEEE.Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.Text