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Realizing integrated prioritized service in the Hadoop cloud system

机译：在Hadoop云系统中实现集成的优先服务

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Cloud computing has profoundly influenced how people receive IT services nowadays. As the cloud offers more and more services to users, the Quality of Service (QoS) in cloud has become an important issue that could determine the success or failure of services on the cloud. Among the aspects of cloud QoS, job performance is an area which most cloud systems often have little or no control over it. To effectively manage job performance in cloud QoS, the collaboration between the cloud system and its underlying operating system is a must. Hadoop is one of the most popular cloud systems used today. Unfortunately, it does not support efficient schemes to manage job performance. Previously, we proposed a new approach, namely PYARN, to enable Hadoop to provide prioritized job scheduling service to help manage job performance in cloud QoS. In this paper, we report our efforts to make PYARN collaborate with PMMDO, a Linux module providing prioritized service we developed earlier. Compared with the original Hadoop, experiment results showed that the cooperation between PYARN and PMMDO could further expedite the execution of prioritized jobs by up to around 30% more than what PYARN could achieve alone. Our integrated system demonstrates that the cloud system and its host operating system should work together to help manage cloud QoS with regard to job performance. (C) 2019 Elsevier B.V. All rights reserved.
机译：如今，云计算已深刻影响着人们如何获得IT服务。随着云为用户提供越来越多的服务，云中的服务质量（QoS）已成为一个重要问题，可以决定云上服务的成败。在云QoS的各个方面中，作业性能是大多数云系统通常对其几乎没有控制的领域。为了有效地管理云QoS中的作业性能，必须在云系统及其底层操作系统之间进行协作。 Hadoop是当今使用的最受欢迎的云系统之一。不幸的是，它不支持有效的方案来管理工作绩效。以前，我们提出了一种新方法，即PYARN，以使Hadoop提供优先的作业调度服务，以帮助管理云QoS中的作业性能。在本文中，我们报告了我们为使PYARN与PMMDO合作而付出的努力，PMMDO是一个Linux模块，提供了我们先前开发的优先服务。与原始Hadoop相比，实验结果表明PYARN和PMMDO之间的合作可以进一步加快优先级作业的执行，其速度比PYARN单独完成的任务高30％左右。我们的集成系统表明，云系统及其主机操作系统应协同工作，以帮助管理有关工作绩效的云QoS。 （C）2019 Elsevier B.V.保留所有权利。

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