期刊
INTEGRATED COMPUTER-AIDED ENGINEERING
卷 22, 期 3, 页码 261-280出版社
IOS PRESS
DOI: 10.3233/ICA-150489
关键词
Scientific workflow; heterogeneous multicluster; scheduling; advance reservation; task duplication; task migration
类别
资金
- National Natural Science Foundation of China [61320106007, 61370207, 61202449, 61300024, 61472080]
- National High-tech RAMP
- D Program of China (863 Program) [2013AA013503]
- China Specialized Research Fund for the Doctoral Program of Higher Education [20110092130002]
- Jiangsu research prospective joint research project [BY2012202, BY2013073-01]
- Jiangsu Provincial Key Laboratory of Network and Information Security [BM2003201]
- Key Laboratory of Computer Network and Information Integration of Ministry of Education of China [93K-9]
Scientific workflow structured as Parallel Task Graphs (PTG) exhibits both data and task parallelism, and arises in scientific as well as in industrial domains. Efficient scheduling of such workflow on a multicluster platform has been a long-standing challenge. Most of previous work on PTG scheduling primarily focused on dedicated multicluster. In this paper, a novel scheduling algorithm known as the Moldable Task Duplication (MTD) is applied to non-dedicated heterogeneous multicluster platform with advance reservations. A novel method for the calculation of dynamic critical path that handles the availability fluctuation of multicluster and the moldability of scientific workflow's data-parallel tasks is proposed. A moldable task duplication strategy with migration of pre-duplicated predecessor tasks is developed to fully exploit the flexibility of data-parallel tasks. Simulations spanning a broad range of scientific workflow and multicluster platform settings are performed in order to verify the proposed approach. The numerical results show that MTD can achieve better average PTG makespan than previous methods in the literature.
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