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Sustainability-aware Resource Provisioning in Data Centers

机译:数据中心中的可持续性感知资源供应

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In the big data era, cloud computing provides an effective usage model for providing computing services to handle diverse data-intensive workloads. Data center capacity planning and resource provisioning policies play a vital role in longterm life cycle management of datacenters. Effective design and management of data center infrastructures while ensuring good performance is critical to minimizing the carbon footprint of the datacenter. Traditional solutions have primarily focused on optimizing data center operational phase impacts including reducing energy cost during the resource management phase. In this paper, we propose a two-phase sustainability-aware resource allocation and management framework for data center life-cycle management that jointly optimizes the data center manufacturing phase and operational phase impact without impacting the performance and service quality for the jobs. Phase 1 of the proposed approach minimizes data center building phase carbon footprint through a novel manufacturing cost-aware server provisioning plan. In phase 2, the approach minimizes the operational phase carbon footprint using a server lifetime-aware resource allocation scheme and a manufacturing cost-aware replacement plan. The proposed techniques are evaluated through extensive experiments using realistic workloads generated in a data center. The evaluation results show that the proposed framework significantly reduces the carbon footprint in the data center without impacting the performance of the jobs in the workload.
机译:在大数据时代,云计算提供了一种有效的使用模型,用于提供计算服务以处理各种数据密集型工作负载。数据中心容量规划和资源供应政策在数据中心的Longterm生命周期管理中起着重要作用。数据中心基础设施的有效设计和管理,同时确保良好的性能对于最小化数据中心的碳足迹至关重要。传统解决方案主要集中在资源管理阶段期间优化数据中心运营相冲击,包括降低能源成本。在本文中,我们提出了一个两相可持续性感知资源分配和数据中心生命周期管理的管理框架,共同优化数据中心制造阶段和运行相位影响,而不会影响作业的性能和服务质量。所提出的方法的第1阶段通过新颖的制造成本感知服务器供应计划最大限度地减少数据中心构建阶段碳足迹。在阶段2中,该方法使用服务器寿命感知资源分配方案和制造成本感知更换计划最小化操作阶段碳足迹。所提出的技术通过使用数据中心生成的现实工作负载进行广泛的实验来评估。评估结果表明,所提出的框架显着降低了数据中心的碳足迹,而不会影响工作量中作业的性能。

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