CoolCloudSim: Integrating Cooling System Models in CloudSim

Cristian Pintea, Eugen Pintea, Marcel Antal, Claudia Pop, T. Cioara, I. Anghel, I. Salomie
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引用次数: 7

Abstract

This paper addresses the problem of Data Centers (DCs) energy efficiency from a thermal perspective by extending the CloudSim framework to allow simulation and testing of thermal aware resource allocation policies aiming to minimize the cooling system energy consumption. The proposed framework, CoolCloudSim, can be used to develop and test new thermal aware Virtual Machine (VM) allocation strategies aiming to optimize the energy consumption of both cooling system and IT resources while meeting Service Level Agreements (SLAs). The default CloudSim architecture is extended by adding classes which contain mathematical models of the thermal processes within the server room. Furthermore, four new VM allocation policies that consider the cooling system energy consumption are developed based on the thermal and cooling system models. Finally, experiments are run to evaluate various metrics on a set of default CloudSim allocation algorithms and the proposed allocation algorithms. The results show that the proposed algorithms outperform the default CloudSim allocation strategy, Power Aware Best-Fit Decreasing (PABFD), in terms of overall energy consumption and the number of VM migrations, and have on average better results than other existing allocation strategies.
CoolCloudSim:在CloudSim中集成冷却系统模型
本文通过扩展CloudSim框架,从热的角度解决了数据中心(DCs)的能源效率问题,从而允许模拟和测试热感知资源分配策略,旨在最大限度地减少冷却系统的能源消耗。拟议的框架CoolCloudSim可用于开发和测试新的热感知虚拟机(VM)分配策略,旨在优化冷却系统和IT资源的能耗,同时满足服务水平协议(sla)。默认的CloudSim架构是通过添加包含服务器机房内热过程数学模型的类来扩展的。此外,基于热系统和冷系统模型,提出了四种考虑冷却系统能耗的虚拟机分配策略。最后,运行实验来评估一组默认CloudSim分配算法和建议的分配算法上的各种指标。结果表明,所提出的算法在总体能耗和VM迁移数量方面优于默认的CloudSim分配策略Power Aware Best-Fit reduction (PABFD),并且平均优于其他现有的分配策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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