2006 Second IEEE International Conference on E-Science and Grid Computing (E-Science'06) 2006
DOI: 10.1109/e-science.2006.261180
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Grid-Enabled Workflows for Industrial Product Design

Abstract: This paper presents a generic approach for developing and using Grid-based

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Cited by 9 publications
(7 citation statements)
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“…Simulation is nowadays a prerequisite for product design and scientific breakthroughs in most application areas, ranging from pharmacy, weather forecast, biology to climate modeling, that all require extensive simulations and testing [6] [8]. They often need large-scale experiments, including long-lasting runs in the orders of weeks, tested against petabytes volumes of data and will soon run on exascale supercomputers [10] [11] [19].…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Simulation is nowadays a prerequisite for product design and scientific breakthroughs in most application areas, ranging from pharmacy, weather forecast, biology to climate modeling, that all require extensive simulations and testing [6] [8]. They often need large-scale experiments, including long-lasting runs in the orders of weeks, tested against petabytes volumes of data and will soon run on exascale supercomputers [10] [11] [19].…”
Section: Related Workmentioning
confidence: 99%
“…Workflows systems are the support for many e-Science applications [1][6] [8]. Among the most popular systems are Taverna, Kepler, Pegasus, Bonita and many others [11] [15].…”
Section: A the Yawl Workflow Systemmentioning
confidence: 99%
“…As shown in Fig. 3, within a Grid computing environment, each node can be further implemented as a sub-workflow implementing the steps required for accessing and invoking a remote Grid computing resource [18].…”
Section: Data Flowmentioning
confidence: 99%
“…Tsiakkouri et al [10] developed scheduling approaches to adjust a schedule generated by a time optimized heuristic and a cost optimized heuristic to meet users' budget constraints respectively. GRIA (Grid Resources for Industrial Applications) [24] provides various resource allocation strategies for workflow execution based on QoS requirements. In our previous work [9], we have developed algorithms based on the genetic algorithms to minimize either execution cost or time.…”
Section: Related Workmentioning
confidence: 99%