面向海量数字资源管理的FC-SAN性能分析与监测
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摘要
信息爆炸为海量数字资源管理带来的挑战之一就是海量信息的存储问题。以FC-SAN为代表的网络化存储为该挑战提供了新的解决途径。海量数字资源管理的一个典型应用就是大型数字图书馆。FC-SAN系统作为存储基础设施其性能在很大程度上影响着整个数字图书馆应用在访问性能和服务质量上的表现。然而由于组成结构复杂等诸多因素,致使FC-SAN系统性能的有关研究仍处于初级阶段,从理论到工具都十分欠缺。本论文主要致力于解决这一领域中最高的一个层次——FC-SAN系统性能分析和监测的问题,论文的主要内容如下:
通过回顾FC-SAN的典型组成,给出FC-SAN性能分析模型的整体抽象及其适用范围,并在介绍每一组成的运作技术的基础之上给出每一组成的模型抽象与数学描述——即SANMO2模型方法;并通过实例说明了模型的应用与实施方法,对比实例的模型验证结果显示其最大误差率不超过28%。在此基础上,利用该分析模型预测出FC-SAN系统实例在几种典型工作负载下瓶颈会出现在不同位置这一事实,从另一个角度说明了FC-SAN系统性能分析的必要性;并在定位瓶颈的基础上,利用该模型讨论了瓶颈的缓解,提出了次瓶颈(簇)的概念,指出:对存在次瓶颈的系统,必须同时增加所有属于次瓶颈簇的部位的系统资源,才能对系统的性能改善起到有效作用。
基于上述工作,提出一种系统性能监测方法。该方法较之主流的带内方法、带外方法,具有实施代价小、对被监控系统本身影响小、较为独立和公正、相对健壮等优点。由于该方法的有效性很大程度上依赖于分析模型的有效性,具体而言主要包括分析模型的扩展能力以及分析模型的精度。因此本文将SANMO2模型在部分随机I/O、读写请求混合、阵列控制器缓存使能等方面进行了扩展;并结合Round现象为模型进行了校正,同时讨论了校正后模型的适用范围,在该范围内,模型的精确程度提高了近30%(最大误差率降低约8%)。
作为对于分析方法的补充,最后,本文提出一种可以对整个FC-SAN系统进行性能仿真的MMQ模型,用于不同的FC-SAN实例。通过例子,本文还对该模型的仿真实现以及仿真结果的分析和评价进行了说明。
Information Explosion brings a big challenge to the storage system of Massive Digital Resource Management. The networked storage technology, such as FC-SAN, provides a solution for this challenge. One of the typical application domains of Massive Digital Resource Management is the large-scale digital library. As a system infrastructure, FC-SAN and its performance has a critical impact on data access performance and service quality of digital libraries. However, for various reasons, such as complex structure etc., current research on the performance of FC-SAN is still in a preliminary stage in terms of both theoretic works and practical tools. This dissertation, from high-end users’perspective, studies the performance analysis and monitoring issues of FC-SAN system, and presents the results of this study. The main content of the dissertation is as follows:
By investigating the typical components of FC-SAN, we propose an abstract FC-SAN performance analysis model and indicate its application scope. Based on each component’s operation, the model abstracts each component by a mathematic description. This process that we call SANMO2 modeling method is illustrated by a real case. The validation result of the model shows that the maximum error rate is less than 28%. By using this analysis model, we can locate the bottlenecks and the change of bottlenecks for the real case when the case system is under different workload. Besides the bottleneck locating, we also discuss the bottleneck relieving and propose the concept of Secondary Bottleneck (Cluster). We point out that, for a system that contains secondary bottleneck(s), the system resources of the secondary bottleneck cluster should all be increased, so that an effective performance improvement can be achieved.
Based on the above work, a new system performance monitoring method is proposed. Compared with the current in-band method and out-of-band method, this method has several advantages such as low deployment cost, less overhead to the monitored system itself, more independent/impartial and more robust. As the effectiveness of this method depends on the expandability and the precision of theanalysis model, so we discuss this dependence also. We expand the analysis model for the cases of partial random I/O, mixture of read/write requests, and array controller cache enabling, etc. And we adjust the model to accommodate the phenomenon of Round, and discuss the applicable scope of the adjusted model. Within this scope, the model precision is almost improved by 30% (i.e. the maximum error rate is almost decreased by 8%).
As a complementary to the analysis method, finally, we propose a performance simulation model MMQ for the whole FC-SAN system. This model can be applied to different FC-SAN instances. And by a real case, we also illustrate the simulation process and discuss how to analyze and evaluate the simulation results.
通过回顾FC-SAN的典型组成,给出FC-SAN性能分析模型的整体抽象及其适用范围,并在介绍每一组成的运作技术的基础之上给出每一组成的模型抽象与数学描述——即SANMO2模型方法;并通过实例说明了模型的应用与实施方法,对比实例的模型验证结果显示其最大误差率不超过28%。在此基础上,利用该分析模型预测出FC-SAN系统实例在几种典型工作负载下瓶颈会出现在不同位置这一事实,从另一个角度说明了FC-SAN系统性能分析的必要性;并在定位瓶颈的基础上,利用该模型讨论了瓶颈的缓解,提出了次瓶颈(簇)的概念,指出:对存在次瓶颈的系统,必须同时增加所有属于次瓶颈簇的部位的系统资源,才能对系统的性能改善起到有效作用。
基于上述工作,提出一种系统性能监测方法。该方法较之主流的带内方法、带外方法,具有实施代价小、对被监控系统本身影响小、较为独立和公正、相对健壮等优点。由于该方法的有效性很大程度上依赖于分析模型的有效性,具体而言主要包括分析模型的扩展能力以及分析模型的精度。因此本文将SANMO2模型在部分随机I/O、读写请求混合、阵列控制器缓存使能等方面进行了扩展;并结合Round现象为模型进行了校正,同时讨论了校正后模型的适用范围,在该范围内,模型的精确程度提高了近30%(最大误差率降低约8%)。
作为对于分析方法的补充,最后,本文提出一种可以对整个FC-SAN系统进行性能仿真的MMQ模型,用于不同的FC-SAN实例。通过例子,本文还对该模型的仿真实现以及仿真结果的分析和评价进行了说明。
Information Explosion brings a big challenge to the storage system of Massive Digital Resource Management. The networked storage technology, such as FC-SAN, provides a solution for this challenge. One of the typical application domains of Massive Digital Resource Management is the large-scale digital library. As a system infrastructure, FC-SAN and its performance has a critical impact on data access performance and service quality of digital libraries. However, for various reasons, such as complex structure etc., current research on the performance of FC-SAN is still in a preliminary stage in terms of both theoretic works and practical tools. This dissertation, from high-end users’perspective, studies the performance analysis and monitoring issues of FC-SAN system, and presents the results of this study. The main content of the dissertation is as follows:
By investigating the typical components of FC-SAN, we propose an abstract FC-SAN performance analysis model and indicate its application scope. Based on each component’s operation, the model abstracts each component by a mathematic description. This process that we call SANMO2 modeling method is illustrated by a real case. The validation result of the model shows that the maximum error rate is less than 28%. By using this analysis model, we can locate the bottlenecks and the change of bottlenecks for the real case when the case system is under different workload. Besides the bottleneck locating, we also discuss the bottleneck relieving and propose the concept of Secondary Bottleneck (Cluster). We point out that, for a system that contains secondary bottleneck(s), the system resources of the secondary bottleneck cluster should all be increased, so that an effective performance improvement can be achieved.
Based on the above work, a new system performance monitoring method is proposed. Compared with the current in-band method and out-of-band method, this method has several advantages such as low deployment cost, less overhead to the monitored system itself, more independent/impartial and more robust. As the effectiveness of this method depends on the expandability and the precision of theanalysis model, so we discuss this dependence also. We expand the analysis model for the cases of partial random I/O, mixture of read/write requests, and array controller cache enabling, etc. And we adjust the model to accommodate the phenomenon of Round, and discuss the applicable scope of the adjusted model. Within this scope, the model precision is almost improved by 30% (i.e. the maximum error rate is almost decreased by 8%).
As a complementary to the analysis method, finally, we propose a performance simulation model MMQ for the whole FC-SAN system. This model can be applied to different FC-SAN instances. And by a real case, we also illustrate the simulation process and discuss how to analyze and evaluate the simulation results.
引文
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