DDS: A Deadline Driven Workflow Scheduling Algorithm for Hybrid Amazon Instances
| Autor: | Zitai Ma, Shiyou Qian, Jian Cao |
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| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319269788 APSCC |
| DOI: | 10.1007/978-3-319-26979-5_18 |
| Popis: | Workflows can orchestrate multiple applications that need resources to execute. The cloud computing has emerged as an on-demand resource provisioning paradigm, which can support workflow execution. In recent years, Amazon offers a new service option, i.e., EC2 spot instances, whose price is on average more than 75i¾ź% lower than the one of on-demand instances. Therefore, we can make use of spot instances to execute workflows in a cost-efficient way. However, the spot instances is cut off when their price increases and exceeds the customer's bid, which will make the task failed and the execution time becomes unpredictable. We propose a deadline driven scheduling DDS algorithm which is able to use both on-demand and spot instances to reduce the cost while the deadline of workflows can also be guaranteed with a high probability. Especially, we use an attribute, called global weight, to represent the interdependency relations of tasks and schedule the tasks whose interdependent tasks need longer time first to reduce the whole execution time. The experimental results demonstrate that DDS algorithm is effective in reducing cost while satisfying the deadline constraints of workflows. |
| Databáze: | OpenAIRE |
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