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Robust Scheduling of Scientific Workflows with Deadline and Budget Constraints in Clouds
| Citations: | 1 - 0 self |
BibTeX
@MISC{Poola_robustscheduling,
author = {Deepak Poola and Saurabh Kumar Garg and Rajkumar Buyya and Yun Yang and Kotagiri Ramamohanarao},
title = {Robust Scheduling of Scientific Workflows with Deadline and Budget Constraints in Clouds},
year = {}
}
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Abstract
Abstract—Dynamic resource provisioning and the notion of seemingly unlimited resources are attracting scientific workflows rapidly into Cloud computing. Existing works on workflow scheduling in the context of Clouds are either on deadline or cost optimization, ignoring the necessity for robustness. Robust scheduling that handles performance variations of Cloud resources and failures in the environment is essential in the context of Clouds. In this paper, we present a robust scheduling algorithm with resource allocation policies that schedule workflow tasks on heterogeneous Cloud resources while trying to minimize the total elapsed time (makespan) and the cost. Our results show that the proposed resource allocation policies provide robust and fault-tolerant schedule while minimizing makespan. The results also show that with the increase in budget, our policies increase the robustness of the schedule.
Keyphrases
scientific workflow robust scheduling budget constraint resource allocation policy heterogeneous cloud resource robust scheduling algorithm fault-tolerant schedule abstract dynamic resource provisioning cloud resource unlimited resource performance variation workflow task workflow scheduling cost optimization
