Optimizing N-Tier Application Scalability in the Cloud
Optimizing N-Tier Application Scalability in the Cloud
复制标题
优化云中的 N 层应用程序可扩展性
DOI：
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发表时间：
2019
影响因子：
0.6
通讯作者：
Motoyuki Kawaba
中科院分区：
文献类型：
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作者：
Qingyang Wang;Shungeng Zhang;Yasuhiko Kanemasa;C. Pu;Balaji Palanisamy;L. Harada;Motoyuki Kawaba
一个有效的云计算环境需要良好的性能和高效的计算资源。通过使用具有代表性的n层基准应用程序（Rice University Bulletin Board System (RUBBoS)）进行大量实验，我们表明组件服务器中的软资源分配（例如线程池大小和数据库连接池大小）对系统整体性能有显著影响，特别是在高系统利用率场景下。具体地说，相同的软件资源分配在一个硬件配置中可能是一个很好的设置，但在另一个略有不同的硬件配置中可能会出现分配不足或过多的情况，从而导致显著的性能下降。我们还观察到一些有趣的现象，这些现象是由不同层服务器的软资源之间的非平凡依赖所引起的。例如，Apache web服务器中的线程池大小可以限制对下游服务器的并发请求总数，随着工作负载的增加，这会令人惊讶地降低集群Java数据库连接（C-JDBC）集群中间件的中央处理单元（CPU）利用率。为了提供系统中各层的全局最优（或接近最优）软资源分配，我们提出了一种实用的迭代解决方法，该方法将软资源感知排队网络模型与每个组件服务器的细粒度测量数据相结合。我们的研究结果表明，要真正扩展复杂的分布式系统，如n层web应用程序，在云中具有预期的性能，我们需要仔细管理系统中的软资源分配。
An effective cloud computing environment requires both good performance and high efficiency of computing resources. Through extensive experiments using a representative n-tier benchmark application (Rice University Bulletin Board System (RUBBoS)), we show that the soft resource allocation (e.g., thread pool size and database connection pool size) in component servers has a significant impact on the overall system performance, especially at high system utilization scenarios. Concretely, the same software resource allocation can be a good setting in one hardware configuration and then becomes an either under- or over-allocation in a slightly different hardware configuration, causing a significant performance drop. We have also observed some interesting phenomena that were caused by the non-trivial dependencies between the soft resources of servers in different tiers. For instance, the thread pool size in an Apache web server can limit the total number of concurrent requests to the downstream servers, which surprisingly decreases the Central Processing Unit (CPU) utilization of the Clustered Java Database Connectivity (C-JDBC) clustering middleware as the workload increases. To provide a globally optimal (or near-optimal) soft resource allocation of each tier in the system, we propose a practical iterative solution approach by combining a soft resource aware queuing network model and the fine-grained measurement data of every component server. Our results show that to truly scale complex distributed systems such as n-tier web applications with expected performance in the cloud, we need to carefully manage soft resource allocation in the system.
CEDULE：云计算中突发性能的调度框架
DOI：
10.1109/icac.2018.00024
发表时间：
2018
期刊：
2018 IEEE International Conference on Autonomic Computing (ICAC
影响因子：
--
作者：
Ali, Ahsan;Pinciroli, Riccardo;Yan, Feng;Smirni, Evgenia
通讯作者：
Smirni, Evgenia