Mining Multi-attribute Sequential Pattern in Onboard Failure Logging
Onboard Failure Logging(OBFL)is an advanced feature of hardware system.It records failure-related data which is useful for failure analysis process and system reliability improvement.OBFL records are event sequences with multi-attributes.There are lots of algorithms proposed for sequential pattern mining,whereas not much effort has been made to use attribute held by events.However such attributes are critical for failure pattern detecting in failure analysis process.In this paper,we point out the problem of mining multi-attribute sequential pattern in OBFL dataset and propose a new algorithm,called MA-PrefixSpan,to solve it.Finally,we design the OBFL Analysis System to generate the real world OBFL datasets and apply MA-PrefixSpan to mine the failure pattern.The results show that the algorithm can effectively locate the multi-attribute failure patterns which are correlated with failure trends.
Sequential Pattern Mining Multi-attribute OBFL Onboard Failure Logging Failure Analysis
Min Zhu Yicheng Li Shaoqin Chen
Failure Analysis Department Technology and Quality,CISCO Shanghai,China
国际会议
厦门
英文
653-658
2014-08-19（万方平台首次上网日期，不代表论文的发表时间）