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Efficient Fault Tree Analysis of Complex Fault Tolerant Multiple-Phased Systems
  • ISSN号:1002-0470
  • 期刊名称:《高技术通讯》
  • 时间:0
  • 分类:TP302.8[自动化与计算机技术—计算机系统结构;自动化与计算机技术—计算机科学与技术]
  • 作者机构:Department of Computer Science and Technology Harbin Institute of Technology, Department of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
  • 相关基金:the National Natural Science Foundation of China (No. 60503015)
中文摘要:

Fault tolerant multiple phased systems (FTMPS), i.e., systems whose critical components are independently replicated and whose operational life can be partitioned in a set of disjoint periods, are called "phases". Because of their deployment in critical applications, their reliability analysis is a task of primary relevance to validate the designs. Fault tree analysis based on binary decision diagram (BDD) is one of the most commonly used techniques for FTMPS reliability analysis. To utilize the technique the fault tree structure of FTMPS needs to be converted into the corresponding BDD format. Our research work shows that the system BDD generation algorithms presented in the literature are too inefficient to be used for industrial complex FTPMS because of the problems, such as variable ordering and combination of large BDDs. This paper presents a more efficient approach consisting of a flatting pre-processing technique, a proved efficient ordering heuristic and a bottom-up generation algorithm. The approach tries to combine share-variable BDDs by complex combination operation firstly and then combine no-share-variable BDDs using simple combination operation, thus to alvoid the intensive computations caused by large BDD combination operations. An example FTMPS is analyzed to illustrate the advantages of our approach.

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期刊信息
  • 《高技术通讯》
  • 北大核心期刊(2011版)
  • 主管单位:中华人民共和国科学科技部
  • 主办单位:中国科学技术信息研究所
  • 主编:赵志耘
  • 地址:北京市三里河路54号
  • 邮编:100045
  • 邮箱:hitech@istic.ac.cn
  • 电话:010-68514060 68598272
  • 国际标准刊号:ISSN:1002-0470
  • 国内统一刊号:ISSN:11-2770/N
  • 邮发代号:82-516
  • 获奖情况:
  • 《中国科学引文数据》刊源,《中国科技论文统计与分析》刊源
  • 国内外数据库收录:
  • 美国化学文摘(网络版),荷兰文摘与引文数据库,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),英国英国皇家化学学会文摘
  • 被引量:12178