关于规模经济对科学界影响的调查

S. Verma, R. Satao
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引用次数: 3

摘要

云计算通常被描述为一种计算,它依赖于提供计算资源,而不是使用邻近的服务器或单独的小工具来处理应用程序。资源供应商为客户提供适应性强的资源。在本文中,我们建议发现中小型科学社区是否可以利用规模经济作为云计算的一部分,以获得其优势。在本文中,我们提出了一个公共云模型,将任何开放云供应商的适应性资源出租给中小型研究机构。在这种公共云模型的前提下,我们正在实现一种新的策略来处理云上的异构科学工作负载。本文考虑了两种平均工作负载:高吞吐量计算(HTC)和多任务计算(MTC)。我们负责系统的工作负载可以有效地节省这两种工作负载的总资源利用率。我们提出了一种新的调度技术,“早期帐户过期优先与轮询(EAEP-RR)调度”,以处理云上的请求。最后,我们可以假设我们的例程可以从云环境中的规模经济中使科学界受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A survey on the impact of economies of scale on scientific communities
Cloud computing is commonly characterized as a sort of computing that depends on offering computing resources instead of having neighborhood servers or individual gadgets to handle applications. The resource suppliers give adaptable resources to the client. In this paper, we propose to discover it out whether the little or medium scale scientific communities can utilize the economies of scale as a part of the cloud for its advantages. In this paper, we propose a Public Cloud model for leasing the adaptable resources from any open cloud supplier to the little or medium scale research associations. On the premise of this Public Cloud model, we are actualizing a novel strategy to handle the heterogeneous scientific workload on the cloud. The two average workloads are contemplated in this paper: High Throughput Computing (HTC) and Many Task Computing (MTC). Our workload taking care of the system can spare the aggregate resource utilization in both these workloads viably. We are proposing a novel scheduling technique, “Earlier Account Expire Prioritized with Round Robin (EAEP-RR) scheduling”, to handle the requests at cloud. At last, we can presume that our routines can advantage the scientific communities from the economies of scale in the cloud environment.
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