Numerical transient analysis of Markov models
Computers and Operations Research
Sensitivity analysis of reliability and performability measures for multiprocessor systems
SIGMETRICS '88 Proceedings of the 1988 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Performance and reliability modeling using Markov regenerative stochastic Petri nets
Performance and reliability modeling using Markov regenerative stochastic Petri nets
Phased-mission system analysis using Boolean algebraic methods
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Markov regenerative stochastic Petri nets
Performance '93 Proceedings of the 16th IFIP Working Group 7.3 international symposium on Computer performance modeling measurement and evaluation
A Modeling Framework to Implement Preemption Policies in Non-Markovian SPNs
IEEE Transactions on Software Engineering
A Characterization of the Stochastic Process Underlying a Stochastic Petri Net
IEEE Transactions on Software Engineering
Analytical Modelling and Evaluation of Phased-Mission Systems for Space Applications
HASE '97 Proceedings of the 2nd High-Assurance Systems Engineering Workshop
Extended Stochastic Petri Nets: Applications and Analysis
Performance '84 Proceedings of the Tenth International Symposium on Computer Performance Modelling, Measurement and Evaluation
Transient Analysis of Deterministic and Stochastic Petri Nets
Proceedings of the 14th International Conference on Application and Theory of Petri Nets
DEEM: A Tool for the Dependability Modeling and Evaluation of Multiple Phased Systems
DSN '00 Proceedings of the 2000 International Conference on Dependable Systems and Networks (formerly FTCS-30 and DCCA-8)
MASCOTS '95 Proceedings of the 3rd International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
Dependability Modeling and Evaluation of Phased Mission Systems: A DSPN Approach
DCCA '99 Proceedings of the conference on Dependable Computing for Critical Applications
Markov regenerative SPN with non-overlapping activity cycles
IPDS '95 Proceedings of the International Computer Performance and Dependability Symposium on Computer Performance and Dependability Symposium
IEEE Transactions on Computers
Analysis of a Redundant Architecture for Critical Infrastructure Protection
Architecting Dependable Systems V
An integrated framework for the dependability evaluation of distributed mobile applications
Proceedings of the 2008 RISE/EFTS Joint International Workshop on Software Engineering for Resilient Systems
Modeling aircraft operational reliability
SAFECOMP'11 Proceedings of the 30th international conference on Computer safety, reliability, and security
Dependability evaluation of web service-based processes
EPEW'06 Proceedings of the Third European conference on Formal Methods and Stochastic Models for Performance Evaluation
A modular approach for model-based dependability evaluation of a class of systems
ISAS'04 Proceedings of the First international conference on Service Availability
Investigating dynamic reliability and availability through state-space models
Computers & Mathematics with Applications
Application of a reliability model generator to a pressure tank system
International Journal of Automation and Computing
A component-based solution for reducible Markov regenerative processes
Performance Evaluation
| Hi-index | 14.99 |
This study deals with model-based dependability transient analysis of phased mission systems. A review of the studies in the literature showed that several aspects of multiphased systems pose challenging problems to the dependability evaluation methods and tools. To attack the weak points of the state-of-the-art we propose a modeling methodology that exploits the power of the class of Markov regenerative stochastic Petri net models. By exploiting the techniques available in the literature for the analysis of the Markov Regenerative Processes, we obtain an analytical solution technique with a low computational complexity, basically dominated by the cost of the separate analysis of the system inside each phase. Last, the existence of analytical solutions allows us to derive the sensitivity functions of the dependability measures, thus providing the dependability engineer with additional means for the study of phased mission systems.