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In cloud, do MTC or HTC service providers benefit from the economies of scale?

机译:在云中,MTC或HTC服务提供商会从规模经济中受益吗?

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Cloud computing, which is advocated as an economic platform for daily computing, has become a hot topic for both industrial and academic communities in the last couple of years. The basic idea behind cloud computing is that resource providers, which own the cloud platform, offer elastic resources to end users. In this paper, we intend to answer one key question to the success of cloud computing: in cloud, do many task computing (MTC) or high throughput computing (HTC) service providers, which offer the corresponding computing service to end users, benefit from the economies of scale? To the best of our knowledge, no previous work designs and implements the enabling system to consolidate MTC and HTC workloads on the cloud platform and no one answers the above question. Our research contributions are threefold: first, we propose an innovative usage model, called dynamic service provision (DSP) model, for MTC or HTC service providers. In theDSP model, the resource provider provides the service of creating and managing runtime environments for MTC or HTC service providers, and consolidates heterogeneous MTC or HTC workloads on the cloud platform; second, based on the DSP model, we design and implement Dawningcloud, which provides automatic management for heterogeneous workloads; third, a comprehensive evaluation of Dawningcloud has been performed in an emulatation experiment. We found that for typical workloads, in comparison with the previous two cloud solutions, Dawningcloud saves the resource consumption maximally by 46.4% (HTC) and 74.9% (MTC) for the service providers, and saves the total resource consumption maximally by 29.7% for the resource provider. At the same time, comparing with the traditional solution that provides MTC or HTC services with dedicated systems, Dawningcloud is more cost-effective. To this end, we conclude that for typical MTC and HTC workloads, on the cloud platform, MTC and HTC service providers and the resource service provider can benefit from the economies of scale.
机译:在过去的几年中,被认为是日常计算的经济平台的云计算已成为工业界和学术界的热门话题。云计算背后的基本思想是拥有云平台的资源提供商向最终用户提供弹性资源。在本文中,我们打算回答一个有关云计算成功的关键问题:在云中,可以为许多任务计算(MTC)或高吞吐量计算(HTC)服务提供商提供服务,从而为最终用户提供相应的计算服务,从而从中受益规模经济?据我们所知,以前没有工作来设计和实现支持系统以在云平台上整合MTC和HTC工作负载,并且没有人回答上述问题。我们的研究贡献包括三个方面:首先,我们为MTC或HTC服务提供商提出了一种创新的使用模型,称为动态服务提供(DSP)模型。在DSP模型中,资源提供者为MTC或HTC服务提供者提供创建和管理运行时环境的服务,并在云平台上整合异构MTC或HTC工作负载。其次,基于DSP模型,我们设计并实现了Dawningcloud,它可以为异构工作负载提供自动管理。第三,在乳化实验中对曙光云进行了综合评估。我们发现,对于典型的工作负载,与前两个云解决方案相比,Dawningcloud为服务提供商最大节省了46.4%(HTC)和74.9%(MTC)的资源消耗,对于以下情况,最大节省了29.7%的总资源消耗资源提供者。同时,与为MTC或HTC服务提供专用系统的传统解决方案相比,Dawningcloud更具成本效益。为此,我们得出结论,对于典型的MTC和HTC工作负载,在云平台上,MTC和HTC服务提供商以及资源服务提供商可以从规模经济中受益。

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