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Energy Efficient Scheduling for Multiple Workflows in Cloud Environment

机译:云环境中多个工作流的节能调度

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摘要

Cloud computing makes utility computing possible with pay as you go model. It virtualizes the systems by polling and sharing the resources, thus we need to handle more than one workflow at the same time. Workflow is the standard to represent compute intensive applications in scientific and engineering domain. Hence, in this article, the authors presented the scheduling heuristic for multiple workflows running parallel in the cloud environment with the aim to reduce the energy consumption as it is one of the major concerns of cloud data centers along with the execution performance. In the proposed approach, first clustering is performed to minimize the energy consumption and execution time during communication corresponding to precedence constraint tasks. Then cluster are scheduled is on the best available energy efficient resources. Finally, DVFS is applied in order to reduce energy consumption further when the nodes are in the idle and communication stage. The simulation has been performed on CloudSim and the results show the reduction in energy consumption by up to 42%.
机译:云计算使按需付费模型可以进行公用事业计算。它通过轮询和共享资源来虚拟化系统,因此我们需要同时处理多个工作流程。工作流是代表科学和工程领域中计算密集型应用程序的标准。因此,在本文中,作者提出了在云环境中并行运行的多个工作流的调度启发法,旨在降低能耗,因为它是云数据中心关注的主要问题之一,同时还具有执行性能。在提出的方法中,执行第一聚类以最小化与优先约束任务相对应的通信期间的能量消耗和执行时间。然后在最佳可用节能资源上安排群集。最后,当节点处于空闲和通信阶段时,将应用DVFS以进一步降低能耗。在CloudSim上进行了仿真,结果显示能耗降低了多达42%。

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