Abstract
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. When 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 or no service at all. 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) ratio introduced here is a measure for quantifying this collective value. The FISC ratio is a multi-dimensional measure, and may include priorities, versions of a task or data, deadlines, situational mode, security, application- and domain-specific QoS, and dependencies. In addition to being used for evaluating and comparing RMS, the FISC ratio can be incorporated as part of the objective function in a system's scheduling heuristics.
Original language | English |
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Title of host publication | Proceedings - 8th Euromicro Workshop on Parallel and Distributed Processing, EURO-PDP 2000 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 18-27 |
Number of pages | 10 |
ISBN (Electronic) | 0769505007, 9780769505008 |
DOIs | |
Publication status | Published - 2000 |
Externally published | Yes |
Event | 8th Euromicro Workshop on Parallel and Distributed Processing, EURO-PDP 2000 - Rhodos, Greece Duration: 2000 Jan 19 → 2000 Jan 21 |
Publication series
Name | Proceedings - 8th Euromicro Workshop on Parallel and Distributed Processing, EURO-PDP 2000 |
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Other
Other | 8th Euromicro Workshop on Parallel and Distributed Processing, EURO-PDP 2000 |
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Country/Territory | Greece |
City | Rhodos |
Period | 00/1/19 → 00/1/21 |
Bibliographical note
Publisher Copyright:© 2000 IEEE.
ASJC Scopus subject areas
- General Computer Science