Minimizing Energy Consumption Scheduling Algorithm of Workflows With Cost Budget Constraint on Heterogeneous Cloud Computing Systems
| Autor: | Lan Wang, Zhicheng Wen, Junfeng Man, Longxin Zhang, Mansheng Xiao |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
General Computer Science
Computer science Distributed computing Cloud computing 02 engineering and technology computer.software_genre Task (project management) Scheduling (computing) energy consumption 0202 electrical engineering electronic engineering information engineering General Materials Science Budget constraint business.industry heterogeneous cloud computing systems General Engineering 020206 networking & telecommunications Energy consumption Workflow Cost budget constraint Virtual machine Spare part 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering business computer lcsh:TK1-9971 Workflow application workflow application |
| Zdroj: | IEEE Access, Vol 8, Pp 205099-205110 (2020) |
| ISSN: | 2169-3536 |
| Popis: | Cloud computing is a promising platform to conduct large-scale workflow applications according to the pay-per-use model. Minimizing the energy consumption of precedence constrained workflows with cost budget constraints has become one of the popular topics in cloud data centers. Most existing scheduling algorithms mainly consider execution time or cost of a given workflow application under a budget constraint; however, these algorithms do not adequately consider energy saving. A reducing energy consumption strategy using a critical task remapping (RMREC) algorithm is proposed in this study. This algorithm is decomposed into two phases: energy consumption reduction and critical task remapping. In the first phase, the adjustable cost budget and spare cost are determined on the basis of cost budget, critical task path, and adjustable budget factor. All workflow tasks are further allocated to virtual machines (VMs) with the lowest energy consumption to achieve preliminary mapping between tasks and VMs while satisfying the adjustable cost budget constraint. In the second phase, critical tasks are remapped to VMs according to spare cost to decrease energy consumption caused by task migration. Experiments on two types of workflow applications with different scales demonstrate that the presented RMREC algorithm effectively reduces energy consumption without violating cost budget constraints compared with existing algorithms. |
| Databáze: | OpenAIRE |
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