Towards self-healing web services composition

Guoquan Wu, Jun Wei, Tao Huang
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引用次数: 10

Abstract

To achieve self-healing web services composition, much work has been studied in the area of web services composition recently. However, most work addresses the problem of runtime monitoring, diagnosis and recovery in isolation. What is missing, however, is a unified solution that can be used to tackle this challenge in a principled manner. This paper presents a fresh view on self-healing web services composition. In particular, rather than building baseline system model a priori, we advocate using statistical learning theory(SLT) technique to extract it by observing the behavior of web services composition and locate the potential anomaly.
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走向自修复的web服务组合
为了实现自修复的web服务组合,最近在web服务组合领域进行了大量的研究。但是,大多数工作都是孤立地解决运行时监视、诊断和恢复问题。然而,目前缺少的是一种统一的解决办法,可以用来以有原则的方式应对这一挑战。本文提出了一种关于自修复web服务组合的新观点。特别是,我们提倡使用统计学习理论(SLT)技术,而不是先验地构建基线系统模型,通过观察web服务组合的行为来提取它,并定位潜在的异常。
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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