DCloud: Deadline-Aware Resource Allocation for Cloud Computing Jobs
DCloud: Deadline-Aware Resource Allocation for Cloud Computing Jobs
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DOI：
10.1109/tpds.2015.2489646
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发表时间：
2016-08
影响因子：
5.3
通讯作者：
Dan Li;Congjie Chen;Junjie Guan;Y. Zhang;Jing Zhu;Ruozhou Yu
中科院分区：
文献类型：
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作者：
Dan Li;Congjie Chen;Junjie Guan;Y. Zhang;Jing Zhu;Ruozhou Yu
随着云计算的巨大增长，为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。虽然最近的许多提案都侧重于保证云中的工作性能(特别注意网络带宽)，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，它利用云计算作业的(软)截止日期在数据中心实现灵活高效的资源利用。在作业的截止期要求有保证的情况下，DCloud在资源分配上同时采用了时间滑动(推迟作业启动时间)和带宽伸缩(调整与虚拟机关联的带宽)，以便更好地将分配给作业的资源与云上的剩余资源相匹配。广泛的模拟和试验台实验表明，DCloud可以接受比现有解决方案更多的工作，并以更少的个体租户成本显著增加云提供商的收入。
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.