DCSim:云数据中心的散热节能虚拟机分配框架

Priyank Bhandia, R. S. Anupindi, Pavan Yekbote, N. Singh, H. L. Phalachandra, D. Sitaram
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引用次数: 2

摘要

数字内容的爆炸式增长导致了为云数据中心中的各种应用程序提供和管理大量资源。这些大型云数据中心的能源消耗日益受到关注,占全球电力消耗的1.3%。数据中心的冷却占这一能耗的40%。在可用于研究数据中心能耗的各种机制中,基于仿真的方法非常流行。在本文中,我们提出DCSim,一个可配置的扩展CloudSim,一个广泛使用的云基础设施和模拟框架。CloudSim提供了粗略的功率模型来计算给定工作负载下数据中心的总能耗,但是没有提供将数据中心拓扑和当前冷却面积纳入该功率模型的因素。这使得在CloudSim中构建智能制冷能源感知分配策略变得困难。在DCSim中,我们引入了一种新颖的数据中心模型,通过封装机架、通道、扇区和区域(统称为DCObjects)的概念来解决CloudSim的缺点。我们还提供了对这些dobject的冷却进行建模的功能。这使得针对工作负载的冷却感知资源配置的研究变得更加容易。所提出的DCObjects和数据中心模型被设计为完全可扩展的,以支持该领域的未来发展。在这项工作中,我们还实现了一种支持冷却的VM分配策略,并使用多种算法证明,与不考虑冷却DCObjects的算法相比,这种VM分配策略将有效地减少数据中心总功耗18.18%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DCSim: Cooling Energy Aware VM Allocation Framework for a Cloud Data Center
Explosion of digital content has resulted in large amounts of resources being provisioned and managed for various applications in cloud Data Centers. Energy consumption in these large Cloud Data Centers is a rising concern, accounting for 1.3% of the worlds electricity consumption [1]. Data Center cooling accounts for 40% of this energy consumption [2]. Of the various mechanisms available for studying the energy consumption in Data Centers, a simulation based approach is quite popular. In this paper, we propose DCSim, a configurable extension to CloudSim, a popularly used cloud infrastructure and simulation framework. CloudSim provides coarse power models to calculate total energy consumption in a Data Center for a given workload, but has no provision to factor in the Data Center topology and current cooled area into this power model. This makes building intelligent cooling energy aware allocation policies in CloudSim difficult. In DCSim, we introduce a novel Data Center model that addresses the shortcomings of CloudSim by encapsulating concepts of Racks, Aisles, Sectors and Zones (collectively referred to as DCObjects). We also provide the capability to model the cooling of these DCObjects. This makes the study of cooling aware resource provisioning for workloads easier. The DCObjects and the Data Center model presented are designed to be fully extensible to support future developments in this area. In this work we also implement a Cooling aware VM allocation policy, and demonstrate using multiple algorithms, that this VM allocation policy will effectively reduce the total Data Center power consumption by 18.18% over an algorithm which does not factor in the cooled DCObjects.
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