EVMDD-based analysis and diagnosis methods of multi-state systems with multi-state components

A multi-state system with multi-state components is a model of systems, where performance, capacity, or reliability levels of the systems are represented as states. It usually has more than two states, and thus can be considered as a multi-valued function, called a structure function. Since many structure functions are monotone increasing, their multi-state systems can be represented compactly by edge-valued multi-valued decision diagrams (EVMDDs). This paper presents an analysis method of multi-state systems with multi-state components using EVMDDs. Experimental results show that, by using EVMDDs, structure functions can be represented more compactly than existing methods using ordinary MDDs. Further, EVMDDs yield comparable computation time for system analysis. This paper also proposes a new diagnosis method using EVMDDs, and shows that the proposed method can infer the most probable causes for system failures more efficiently than conventional methods based on Bayesian networks.Japan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and Technology (MEXT)Hiroshima City UniversityGrant-in Aid No. 2500050 (MEXT)Grant no. 0206 (HCU)Grant in Aid for Scientific Research (JSPS

Some extensions to reliability modeling and optimization of networked systems

Ph.DDOCTOR OF PHILOSOPH

EVMDD-Based Analysis and Diagnosis Methods of Multi-State Systems with Multi-State Components *

A multi-state system with multi-state components is a model of systems, where performance, capacity, or reliability levels of the systems are represented as states. It usually has more than two states, and thus can be considered as a multi-valued function, called a structure function. Since many structure functions are monotone increasing, their multi-state systems can be represented compactly by edge-valued multivalued decision diagrams (EVMDDs). This paper presents an analysis method of multi-state systems with multi-state components using EVMDDs. Experimental results show that, by using EVMDDs, structure functions can be represented more compactly than existing methods using ordinary MDDs. Further, EVMDDs yield comparable computation time for system analysis. This paper also proposes a new diagnosis method using EVMDDs, and shows that the proposed method can infer the most probable causes for system failures more efficiently than conventional methods based on Bayesian networks

Computing system reliability modeling, analysis, and optimization

Ph.DDOCTOR OF PHILOSOPH

OBDD-Based Evaluation of Reliability and Importance Measures for Multistate Systems Subject to Imperfect Fault Coverage

Algorithms for evaluating the reliability of a complex system such as a multistate fault-tolerant computer system have become more important recently. They are designed to obtain the complete results quickly and accurately even when there exist a number of dependencies such as shared loads (reconfiguration), degradation, and common-cause failures. This paper presents an efficient method based on Ordered Binary Decision Diagram (OBDD) for evaluating the multistate system reliability and the Griffith’s importance measures which can be regarded as the importance of a system-component state of a multistate system subject to imperfect fault-coverage with various performance requirements. This method combined with the conditional probability methods can handle the dependencies among the combinatorial performance requirements of system modules and find solutions for multistate imperfect coverage model. The main advantage of the method is that its time complexity is equivalent to that of the methods for perfect coverage model and it is very helpful for the optimal design of a multistate fault-tolerant system