IEEE Transactions on Computers
Probability and statistics with reliability, queuing and computer science applications
Probability and statistics with reliability, queuing and computer science applications
Introducation to stochastic Petri nets
Lectures on formal methods and performance analysis
Markov Regenerative Stochastic Petri Nets to Model and Evaluate Phased Mission Systems Dependability
IEEE Transactions on Computers
Stepwise Construction and Refinement of Dependability Models
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
FTCS '95 Proceedings of the Twenty-Fifth International Symposium on Fault-Tolerant Computing
Service-Level Availability Estimation of GPRS
IEEE Transactions on Mobile Computing
Model-based evaluation of a radio resource management system for wireless networks
Proceedings of the 1st conference on Computing frontiers
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Modeling for dependability and performance evaluation has proven to be a useful and versatile approach in all the phases of the system life cycle. Indeed, a widely used approach in performability modeling is to describe the system by state space models (like Markov models). However, for large systems, the state space of the system model may result extremely large, making it very hard to solve. Taking advantage of the characteristics of a particular class of systems, this paper develops a methodology to construct an efficient, scalable and easily maintainable architectural model for such class, especially tailored to dependability analysis. Although limited to the class considered, the proposed methodology shows very attractive because of its ability to master complexity, both in the model design phase and, then, in its solution. A representative case study is also included.