面向服务体系结构中响应时间不稳定性的真实分布

A. Gorbenko, V. Kharchenko, Seyran Mamutov, O. Tarasyuk, Yuhui Chen, A. Romanovsky
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引用次数: 13

摘要

本文报告了我们对一个复杂的系统生物学网络服务进行基准测试的实践经验,并研究了其行为的不稳定性和由通信介质引起的延迟。我们给出了统计数据分析和分布的结果,这些结果符合并预测了在Internet上构建的面向服务的体系结构(soa)典型的响应时间不稳定性。实验表明,目标电子科学Web服务(WS)的请求处理时间比网络往返时间具有更高的不稳定性。研究发现,通过使用特定的理论分布,在短时间间隔内,请求处理时间可以比网络往返时间更好地表示。此外,往返时间的概率分布序列的某些特征使得它们在理论上特别难以拟合。本文中报告的实验工作支持了我们的观点,即处理SOA和web服务本质中固有的不确定性是构建可靠的面向服务系统的主要挑战之一。特别是,这种不确定性表现为非常不稳定的web服务响应时间和难以预测的Internet数据传输延迟。我们的发现表明,考虑的实验数据越多,分布近似就越不精确。本文最后讨论了在此类实验中使用的分析技术的经验教训,数据的有效性,不确定性的主要原因和可能的补救措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real Distribution of Response Time Instability in Service-Oriented Architecture
is paper reports our practical experience of benchmarking a complex System Biology Web Service, and investigates the instability of its behaviour and the delays induced by the communication medium. We present the results of our statistical data analysis and distributions which fit and predict the response time instability typical of Service-Oriented Architectures (SOAs) built over the Internet. Our experiment has shown that the request processing time of the target e-science Web Service (WS) has a higher instability than the network round trip time. It has been found that by using a particular theoretical distribution, within short time intervals the request processing time can be represented better than the network round trip time. Moreover, certain characteristics of the probability distribution series of the round trip time make it particularly difficult to fit them theoretically. The experimental work reported in the paper supports our claim that dealing with the uncertainty inherent in the very nature of SOA and WSs is one of the main challenges in building dependable service-oriented systems. In particular, this uncertainty exhibits itself through very unstable web service response times and Internet data transfer delays that are hard to predict. Our findings indicate that the more experimental data is considered the less precise distributional approximations become. The paper concludes with a discussion of the lessons learnt about the analysis techniques to be used in such experiments, the validity of the data, the main causes of uncertainty and possible remedial actions.
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