An analytical model for multi-tier internet services and its applications
An analytical model for multi-tier internet services and its applications
复制标题
DOI：
10.1145/1064212.1064252
复制
发表时间：
2005-06
期刊：
影响因子：
--
通讯作者：
B. Urgaonkar;G. Pacifici;P. Shenoy;M. Spreitzer;A. Tantawi
中科院分区：
文献类型：
--
作者：
B. Urgaonkar;G. Pacifici;P. Shenoy;M. Spreitzer;A. Tantawi
由于许多互联网应用程序采用多层体系结构，因此在本文中，我们重点讨论此类应用程序的行为的分析建模问题。我们提出了一个基于队列网络的模型，其中队列代表应用的不同层。我们的模型足够通用，可以捕获(I)具有显著不同性能特征的层的行为和(Ii)应用程序特性，如基于会话的工作负载、并发限制和中间层的缓存。我们使用在Linux服务器集群上运行的真实多层应用程序来验证我们的模型。我们的实验表明，我们的模型忠实地捕获了这些应用程序在许多工作负载和配置下的性能。对于各种场景，包括在其中一个应用层进行缓存的场景，我们的模型预测的平均响应时间在观察到的平均响应时间的95%可信区间内。我们的实验还证明了该模型在动态容量供应、性能预测、瓶颈识别和会话监管方面的有效性。在一个场景中，请求到达率从不到1500个请求/分钟增加到近4200个请求/分钟，使用我们的模型的动态预配置技术能够通过将两个应用层的容量分别增加2倍和3.5倍来维持响应时间目标。
Since many Internet applications employ a multi-tier architecture, in this paper, we focus on the problem of analytically modeling the behavior of such applications. We present a model based on a network of queues, where the queues represent different tiers of the application. Our model is sufficiently general to capture (i) the behavior of tiers with significantly different performance characteristics and (ii) application idiosyncrasies such as session-based workloads, concurrency limits, and caching at intermediate tiers. We validate our model using real multi-tier applications running on a Linux server cluster. Our experiments indicate that our model faithfully captures the performance of these applications for a number of workloads and configurations. For a variety of scenarios, including those with caching at one of the application tiers, the average response times predicted by our model were within the 95% confidence intervals of the observed average response times. Our experiments also demonstrate the utility of the model for dynamic capacity provisioning, performance prediction, bottleneck identification, and session policing. In one scenario, where the request arrival rate increased from less than 1500 to nearly 4200 requests/min, a dynamic provisioning technique employing our model was able to maintain response time targets by increasing the capacity of two of the application tiers by factors of 2 and 3.5, respectively.