Scheduling Scientific Workflow Applications with Deadline and Budget Constraints Using Genetic Algorithms
Grid technologies have progressed towards a service‐oriented paradigm that enables a new way of service provisioning based on utility computing models, which are capable of supporting diverse computing services. It facilitates scientific applications to take advantage of computing resources distribu...
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| Vydané v: | Scientific programming Ročník 14; číslo 3-4; s. 217 - 230 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
01.01.2006
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| ISSN: | 1058-9244, 1875-919X |
| On-line prístup: | Získať plný text |
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| Shrnutí: | Grid technologies have progressed towards a service‐oriented paradigm that enables a new way of service provisioning based on utility computing models, which are capable of supporting diverse computing services. It facilitates scientific applications to take advantage of computing resources distributed world wide to enhance the capability and performance. Many scientific applications in areas such as bioinformatics and astronomy require workflow processing in which tasks are executed based on their control or data dependencies. Scheduling such interdependent tasks on utility Grid environments need to consider users′ QoS requirements. In this paper, we present a genetic algorithm approach to address scheduling optimization problems in workflow applications, based on two QoS constraints, deadline and budget. |
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| Bibliografia: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Conference-1 ObjectType-Feature-3 content type line 23 SourceType-Conference Papers & Proceedings-2 ObjectType-Feature-1 |
| ISSN: | 1058-9244 1875-919X |
| DOI: | 10.1155/2006/271608 |