GSPM models: sensitivity analysis and applications
ACM-SE 28 Proceedings of the 28th annual Southeast regional conference
Phased-mission system analysis using Boolean algebraic methods
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
The UltraSAN modeling environment
Performance Evaluation - Special issue: performance modeling tools
Performance Modelling with Deterministic and Stochostic Petri Nets
Performance Modelling with Deterministic and Stochostic Petri Nets
Analytical Modelling and Evaluation of Phased-Mission Systems for Space Applications
HASE '97 Proceedings of the 2nd High-Assurance Systems Engineering Workshop
SPNP: Stochastic Petri Net Package
PNPM '89 The Proceedings of the Third International Workshop on Petri Nets and Performance Models
Sensitivity Analysis of Deterministic and Stochastic Petri Nets
MASCOTS '93 Proceedings of the International Workshop on Modeling, Analysis, and Simulation On Computer and Telecommunication Systems
Performance Modeling Using DSPNexpress
Performance Evaluation of Computer and Communication Systems, Joint Tutorial Papers of Performance '93 and Sigmetrics '93
Transient Analysis of Deterministic and Stochastic Petri Nets
Proceedings of the 14th International Conference on Application and Theory of Petri Nets
Dependability Modeling and Evaluation of Phased Mission Systems: A DSPN Approach
DCCA '99 Proceedings of the conference on Dependable Computing for Critical Applications
Tuning of Database Audits to Improve Scheduled Maintenance in Communication Systems
SAFECOMP '01 Proceedings of the 20th International Conference on Computer Safety, Reliability and Security
SAFECOMP '01 Proceedings of the 20th International Conference on Computer Safety, Reliability and Security
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In this paper we present a new modelling approach for dependability evaluation and sensitivity analysis of Scheduled Maintenance Systems, based on a Deterministic and Stochastic Petri Net approach. The DSPN approach offers significant advantages in terms of easiness and clearness of modelling with respect to the existing Markov chain based tools, drastically limiting the amount of user-assistance needed to define the model. At the same time, these improved modelling capabilities do not result in additional computational costs. Indeed, the evaluation of the DSPN model of SMS is supported by an efficient and fully automatable analytical solution technique for the time-dependent marking occupation probabilities. Moreover, the existence of such explicit analytical solution allows to obtain the sensitivity functions of the dependability measures with respect to the variation of the parameter values. These sensitivity functions can be conveniently employed to analytically evaluate the effects that parameter variations have on the measures of interest.