Memory Degradation Analysis in Private and Public Cloud Environments

E. Andrade, F. Machida, R. Pietrantuono, Domenico Cotroneo
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引用次数: 2

Abstract

Memory degradation trends have been observed in many continuously running software systems. Applications running on cloud computing can also suffer from such memory degradation that may cause severe performance degradation or even experience a system failure. Therefore, it is essential to monitor such degradation trends and find the potential causes to provide reliable application services on cloud computing. In this paper, we consider both private and public cloud environments for deploying an image classification system and experimentally investigate the memory degradation that appeared in these environments. The degradation trends in the available memory statistics are confirmed by the Mann-Kendall test in both cloud environments. We apply causal structure discovery methods to process-level memory statistics to identify the causality of the observed memory degradations. Our analytical results identify the suspicious processes potentially leading to memory degradations in public and private cloud environments.
私有云和公有云环境中的内存退化分析
在许多连续运行的软件系统中已经观察到内存退化的趋势。在云计算上运行的应用程序也可能出现内存退化,从而导致严重的性能下降,甚至出现系统故障。因此,必须监控这种退化趋势,并找到在云计算上提供可靠应用程序服务的潜在原因。在本文中,我们考虑了私有云和公共云环境来部署图像分类系统,并实验研究了在这些环境中出现的记忆退化。两种云环境中的Mann-Kendall测试证实了可用内存统计数据的退化趋势。我们将因果结构发现方法应用于进程级内存统计,以识别观察到的内存退化的因果关系。我们的分析结果确定了在公共云和私有云环境中可能导致内存退化的可疑进程。
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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