A Resource Optimization Algorithm of Cloud Data Center Based on Correlated Model of Reliability, Performance and Energy
A Resource Optimization Algorithm of Cloud Data Center Based on Correlated Model of Reliability, Performance and Energy
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基于可靠性、性能和能耗相关模型的云数据中心资源优化算法
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Yangyang Tang
中科院分区：
文献类型：
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作者：
Liang Luo;Hongwei Li;Xiwei Qiu;Yangyang Tang
近年来，云数据中心的能效受到了极大的关注，因为数据中心在运行中往往会消耗大量的能源。现有的大多数能效方法侧重于平衡云基础设施的性能和能耗，但这两个标准并不充分，因为没有考虑作为SLA的关键指标的系统可靠性。事实上，无论是虚拟机(VM)故障还是服务器故障，都不可避免地会中断云服务的执行，最终导致花费更多的时间和精力来完成云服务。本文提出了一种能优化可靠性、系统性能和能耗的资源调度算法。它基于半马尔可夫模型、Laplace-Stieltjes变换和贝叶斯方法的相关建模方法来分析可靠性-性能和可靠性-能量相关性。
Energy efficiency of cloud data centers received significant attention in recent years as data centers often consume huge energy in operation. Most existing energy efficiency methods focus on balancing performance and energy consumption of cloud infrastructure, but these two criteria is inadequate because system reliability, which is the key indicator of the SLA, is not considered. In fact, both virtual machine (VM) failures and server failures inevitably interrupt execution of a cloud service, and eventually result in spending more time and consuming more energy on completing the cloud service. This paper proposes a resource scheduling algorithm that can optimize reliability, system performance and energy consumption. It based on a correlated modeling approach applying Semi-Markov models, the Laplace-Stieltjes transform and a Bayesian approach to analyze reliability-performance and reliability-energy correlations.