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DCloud: Deadline-Aware Resource Allocation for Cloud Computing Jobs

机译:DCloud:云计算作业的截止日期感知资源分配

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With the tremendous growth of cloud computing, it is increasingly critical to provide quantifiable performance to tenants and to improve resource utilization for the cloud provider. Though many recent proposals focus on guaranteeing job performance (with a particular note on network bandwidth) in the cloud, they usually lack efficient utilization  of cloud resource, or vice versa. In this paper we present DCloud, which leverages the (soft) deadlines of cloud computing jobs to enable flexible and efficient resource utilization in data centers. With the deadline requirement of a job guaranteed, DCloud employs both time sliding (postponing the launching time of a job) and bandwidth scaling (adjusting the bandwidth associated with VMs) in resource allocation, so as to better match the resource allocated to the job with the cloud's residual resource. Extensive simulations and testbed experiments show that DCloud can accept much more jobs than existing solutions, and significantly increase the cloud provider's revenue with less cost for individual tenants.
机译:随着云计算的迅猛发展,向租户提供可量化的性能并提高云提供商的资源利用率变得越来越重要。尽管最近的许多提议集中在保证云中的工作性能(特别注意网络带宽)上,但它们通常缺乏对云资源的有效利用,反之亦然。在本文中,我们介绍了DCloud,它利用了云计算作业的(软)截止日期来实现数据中心的灵活高效的资源利用。在保证任务期限的前提下,DCloud在资源分配中同时使用了时间滑动(推迟任务的启动时间)和带宽扩展(调整了与VM相关的带宽),以便更好地匹配分配给任务的资源。云的剩余资源。大量的模拟和测试平台实验表明,DCloud可以接受比现有解决方案更多的工作,并显着增加了云提供商的收入,而单个租户的成本却更低。

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