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A Flexible Multi-Dimensional QoS Performance Measure Framework for Distributed Heterogeneous Systems

By Kim Jong-Kook, Debra A. Hensgen, Taylor Kidd, Howard Jay Siegel, Tim Levin, N. Wayne Porter, Richard F. Freund, David St. John, Cynthia E. Irvine and Viktor K. Prasanna


When users' tasks in a distributed heterogeneous computing environment (e.g.cluster of heterogeneous computers) are allocated resources, the total demand placed on some system resources by the tasks, for a given interval of time, may exceed the availability of those resources. In such a case, some tasks may receive degraded service or be dropped from the system. One part of a measure to quantify the success of a resource management system (RMS) in such a distributed environment is the collective value of the tasks completed during an interval of time, as perceived by the user, application, or policy maker. The Flexible Integrated System Capability (FISC) measure presented here is a measure for quantifying this collective value. The FISC measure is a flexible multidimensional measure, and may include priorities, versions of a task or data, deadlines, situational mode, security, application- and domain-specific QoS, and task dependencies. For an environment where it is important to investigate how well data communication requests are satisfied, the data communication request satisfied can be the basis of the FISC measure instead of tasks completed

Topics: cluster computing, distributed computing, heterogeneous computing, performance metrics, resource
Publisher: Cluster Computing
Year: 2006
OAI identifier: oai:calhoun.nps.edu:10945/7144

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