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Information Science and Technology Center (ISTeC)

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https://hdl.handle.net/10217/195492
These digital collections include materials from ISTeC Distinguished Lectures and Industrial Advisory Council presentations, and publications, grants, and student research posters from ISTeC.

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Browsing Information Science and Technology Center (ISTeC) by Author "Briceño, Luis D., author"

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    Measuring the robustness of resource allocations for distributed domputer systems in a stochastic dynamic environment
    (Colorado State University. Libraries, 2006) Dewri, Rinku, author; Alqudah, Amin, author; Govindasamy, Sudha, author; Janovy, David, author; Sutton, Andrew, author; Ladd, Joshua, author; Prakash, Puneet, author; Renner, Timothy, author; Siegel, Howard Jay, author; Maciejewski, Anthony A., author; Briceño, Luis D., author; Smith, Jay, author; Shestak, Vladimir, author
    Heterogeneous distributed computing systems often must function in an environment where system parameters are subject to variations during operation. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. We present a methodology for quantifying the robustness of resource allocations in a dynamic environment where task execution times vary within predictable ranges and tasks arrive randomly. The methodology is evaluated through measuring the robustness of three different resource allocation heuristics within the context of the stochastically modeled dynamic environment. A Bayesian regression model is fit to the combined results of the three heuristics to demonstrate the correlation between the stochastic robustness metric and the presented performance metric. The correlation results demonstrated the significant potential of the stochastic robustness metric to predict the relative performance of the three heuristics given a common objective function.
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    ItemOpen Access
    Study of an iterative resource allocation technique to minimize machine completion times in a distributed computing system
    (Colorado State University. Libraries, 2006) Oltikar, Mohana, author; Briceño, Luis D., author; Maciejewski, Anthony A., author; Siegel, Howard Jay, author
    Heterogeneous computing (HC) is the coordinated use of different types of machines, networks, and interfaces to maximize the combined performance and/or cost effectiveness. Heuristics for allocating resources in an HC system have different optimization criteria. A common optimization criterion is to minimize the completion time of the last to finish machine (makespan). In some environments, it is useful to minimize the finishing times of the other machines in the system, i.e., those machines that are not the last to finish. Consider a production environment where a set of known tasks are to be mapped to resources off-line before execution begins. In this study, we present an "iterative" approach for decreasing the finishing time of each machine in a given resource allocation, by repeatedly running a mapping heuristic to minimize makespan on all machines and then the non-makespan machines; i.e., ignoring the current makespan machine and the tasks assigned to it. This work identifies heuristics that can offer improvements in the completion time of non-makespan machines using this "iterative" approach.