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Hierarchical SLA-Driven Resource Management for Peak Power-Aware and Energy-Efficient Operation of a Cloud Datacenter

机译:SLA分层驱动的资源管理,可实现峰值功率感知和云数据中心的节能运行

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摘要

In this work, a hierarchical, service level agreement (SLA) based resource management solution for cloud datacenters is presented, which considers the energy non-proportionality of existing servers, peak power constraints, and cooling power consumption. The goal of this resource manager is to minimize the operational cost of the data center. The hierarchical structure of the proposed solution makes the resource management scalable. The proposed resource management solution simultaneously considers server and cooling power consumption, guarantee-based SLA and complexity of the decision making in the resource management of the cloud computing systems. Considering SLA and state of the datacenter in determining the amount of resource that needs to be allocated to applications results in significant reduction of the operational cost in datacenter. The effectiveness of the proposed management scheme compared to previous work is demonstrated using a comprehensive cloud computing simulation tool. The proposed resource management algorithms reduce the operational cost of a datacenter by about 40 percent while satisfying SLA constraints and decrease the run-time of the management algorithms by up to 86 percent with respect to the state of the art centralized management solution.
机译:在这项工作中,提出了一种用于云数据中心的基于分层,服务级别协议(SLA)的资源管理解决方案,其中考虑了现有服务器的能源不成比例,峰值功率约束和冷却功耗。该资源管理器的目标是最小化数据中心的运营成本。所提出的解决方案的分层结构使资源管理具有可扩展性。提出的资源管理解决方案同时考虑服务器和冷却功耗,基于保证的SLA以及云计算系统资源管理中决策的复杂性。在确定需要分配给应用程序的资源量时,考虑SLA和数据中心的状态会大大降低数据中心的运营成本。使用全面的云计算仿真工具证明了与以前的工作相比,所提出的管理方案的有效性。相对于最新的集中式管理解决方案,提出的资源管理算法可在满足SLA约束的同时将数据中心的运营成本降低约40%,并将管理算法的运行时间缩短多达86%。

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