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- W1651185206 abstract "The tremendous parallel computing ability of Cloud computing as a new service provisioning paradigm encourages investigators to research its drawbacks and advantages on processing large-scale scientific applications such as workflows. The current Cloud market is composed of numerous diverse Cloud providers and workflow scheduling is one of the biggest challenges on Multi-Clouds. However, the existing works fail to either satisfy the Quality of Service (QoS) requirements of end users or involve some fundamental principles of Cloud computing such as pay-as-you-go pricing model and heterogeneous computing resources. In this paper, we adapt the Partial Critical Paths algorithm (PCPA) for the multi-cloud environment and propose a scheduling strategy for scientific workflow, called Multi-Cloud Partial Critical Paths (MCPCP), which aims to minimize the execution cost of workflow while satisfying the defined deadline constrain. Our approach takes into account the essential characteristics on Multi-Clouds such as charge per time interval, various instance types from different Cloud providers as well as homogeneous intra-bandwidth vs. Heterogeneous inter-bandwidth. Various well-know workflows are used for evaluating our strategy and the experimental results show that the proposed approach has a good performance on Multi-Clouds." @default.
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- W1651185206 date "2015-05-01" @default.
- W1651185206 modified "2023-09-26" @default.
- W1651185206 title "Cost-Driven Scheduling for Deadline-Constrained Workflow on Multi-clouds" @default.
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- W1651185206 doi "https://doi.org/10.1109/ipdpsw.2015.56" @default.
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