摘要
Web服务组合进程规模的不断增加和复杂性的不断提高都有可能导致服务的运行失败,因此很难确保服务的可靠性。针对传统的基于模型的方法无法处理服务应用系统中状态和行为故障的不确定性问题,提出了一种基于贝叶斯与多故障逻辑推理的诊断方法。该方法使用历史数据构建服务执行矩阵,通过多故障逻辑推理技术获取候选诊断解并利用贝叶斯公式计算候选解的后验概率并排序,最终获得一个最优的诊断结果。相比于传统基于模型的Web服务诊断方法,该方法不仅可以同时定位多个故障,而且能够随着历史数据的增加不断优化诊断结果。实验证明该方法具有很好的诊断效果。
The increasing size and complexity of web service composition process has led to an amplified number of potential failures and makes it harder to ensure service reliability.To localize the faults of undefined service behaviors in service process,we proposed a diagnosis method based on Bayes and multi-faults logic reasoning.On the basis of modeling the service execution matrix by historical data,we combined multi-faults logic reasoning technique with the statistical technique to obtain the diagnosis candidates.By applying Bayes＇ formula to compute the fault probability of each diagnosis candidate,our diagnostic method is able to obtain an asymptotically optimal diagnosis with increasing historical data.Experiments were conducted to evaluate the effectiveness of the method in diagnosing the web services with multi-faults.
出处
《计算机科学》
CSCD
北大核心
2014年第6期225-230,共6页
Computer Science
