在云中，MTC或HTC服务提供商是否从规模经济中受益？
In Cloud, Do MTC or HTC Service Providers Benefit from the Economies of Scale?
摘要：
在本文中，我们打算回答一个关键的问题，云计算的成功：在云中，许多任务计算（MTC）或高吞吐量计算（HTC）服务提供商，提供相应的计算服务的最终用户，受益于规模经济？我们的研究贡献是三方面的：首先，我们提出了一个创新的使用模型，称为动态服务提供（DSP）模型，MTC或HTC服务提供商。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环境的服务，并将异构的MTC或HTC工作负载整合到云平台上;其次，根据DSP模型设计并实现了曙光云，提供异构工作负载的自动管理;再次，通过仿真实验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，曙光云为服务提供商最大节省了46.4%（HTC）和74.9%（MTC）的资源消耗，为资源提供商最大节省了29.7%的总资源消耗。同时，与传统的通过专用系统提供MTC或HTC服务的解决方案相比，曙光云具有更高的成本效益。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提供商可以从规模经济中受益。
英文摘要：
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? Our research contributions are three-fold: first, we propose an innovative usage model, called dynamic service provision (DSP) model, for MTC or HTC service providers. In the DSP 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, according to 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 provider can benefit from the economies of scale.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
