Collective Value QoS: A Performance Measure Framework for Distributed Heterogeneous Networks
Siegel, Howard Jay
Irvine, Cynthia E.
Hensgen, Debra A.
St. John, David.
Prasanna, Viktor K.
Freund, Richard F
Porter, N. Wayne
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When users' tasks in a distributed heterogeneous computing environment are allocated resources, and the total demand placed on system resources by the tasks, for a given interval of time, exceeds the resources available, some tasks will receive degraded service, receive no service at all, or may be dropped from the system. One part of a measure to quantify the success of a resource management system (RMS) in such an environment is the collective value of the tasks completed during an interval of time, as perceived by the user, the application, or the policy maker. For the case where a task may be a data communication request, the collective value of data communication requests that are satisfied during an interval of time is measured. The Flexible Integrated System Capability (FISC) measure defined here is one way of obtaining a multi-dimensional measure for quantifying this collective value. While the FISC measure itself is not sufficient for scheduling purposes, it can be a critical part of a scheduler or a scheduling heuristic. The primary contribution of this work is providing a way to measure the collective value accrued by an RMS using a broad range of attributes and to construct a flexible framework that can be extended for particular problem domains.
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A Flexible Multi-Dimensional QoS Performance Measure Framework for Distributed Heterogeneous Systems Jong-Kook, Kim; Hensgen, Debra A.; Kidd, Taylor; Siegel, Howard Jay; Levin, Tim; Porter, N. Wayne; Freund, Richard F.; St. John, David; Irvine, Cynthia E.; Prasanna, Viktor K. (Cluster Computing, 2006-07-01);When users' tasks in a distributed heterogeneous computing environment (e.g.
Kim, Jong-Kook; Hensgen, Debra A.; Kidd, Taylor; Siegel, Howard Jay; St. John, David; Irvine, Cynthia E.; Levin, Tim; Porter, N.Wayne; Prasanna, Viktor; Freund, Richard F. (Euromicro Workshop on Parallel and Distributed Processing, 1999-05-00);In a distributed heterogeneous computing environment, users' tasks are allocated resources to simultaneously satisfy, to varying degrees, the tasks' different, and possibly conflicting, quality of service (QoS) requirements. ...
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