Abstract
In a distributed heterogeneous computing system, the resources have different capabilities and tasks have different requirements. To maximize the performance of the system, it is essential to assign resources to tasks (match) and order the execution of tasks on each resource (schedule in a manner that exploits the heterogeneity of the resources and tasks. The mapping (defined as matching and scheduling) of tasks onto machines with varied computational capabilities has been shown, in general, to be an NP-complete problem. Therefore, heuristic techniques to find a near-optimal solution to this mapping problem are required. Dynamic mapping is performed when the arrival of tasks is not known a priori. In the heterogeneous environment considered in this study, tasks arrive randomly, tasks are independent (i.e., no communication among tasks), and tasks have priorities and multiple deadlines. This research proposes, evaluates, and compares eight dynamic heuristics. The performance of the best heuristics is 83% of an upper bound.
Original language | English |
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Title of host publication | Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 0769519261, 9780769519265 |
DOIs | |
Publication status | Published - 2003 |
Externally published | Yes |
Event | International Parallel and Distributed Processing Symposium, IPDPS 2003 - Nice, France Duration: 2003 Apr 22 → 2003 Apr 26 |
Publication series
Name | Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003 |
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Other
Other | International Parallel and Distributed Processing Symposium, IPDPS 2003 |
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Country/Territory | France |
City | Nice |
Period | 03/4/22 → 03/4/26 |
Bibliographical note
Publisher Copyright:© 2003 IEEE.
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Theoretical Computer Science
- Software