计算机科学 ›› 2015, Vol. 42 ›› Issue (4): 60-64.doi: 10.11896/j.issn.1002-137X.2015.04.010
贾志淳,邢 星
JIA Zhi-chun and XING Xing
摘要: 随着Web服务以及Web服务组合应用软件在分布式网络中的广泛应用,Web服务的规模和复杂性也在不断地增加,这使得服务在运行过程中可能产生各种故障,因此对服务系统进行及时的故障诊断与排除越来越重要。为了解决在故障诊断中系统模型不完备和历史数据中存在噪音数据这一实际问题,提出一种基于服务行为模型的行为推断诊断方法。该方法通过加权方式结合多种诊断信息构建服务行为模型,应用隐马尔科夫模型中的解码思想推断出与异常执行序列最匹配的正常执行序列,并与观察序列进行比较,从而发现差异定位服务故障。实验表明,该方法应用包含不同噪音比例的诊断信息进行诊断,其诊断准确性均高于传统的服务故障诊断方法。
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