Probabilistic Analysis of Wireless Systems Using Theorem Proving
Electronic Notes in Theoretical Computer Science (ENTCS)
Bisimulation minimisation mostly speeds up probabilistic model checking
TACAS'07 Proceedings of the 13th international conference on Tools and algorithms for the construction and analysis of systems
Model checking Markov chains using Krylov subspace methods: an experience report
EPEW'10 Proceedings of the 7th European performance engineering conference on Computer performance engineering
The ins and outs of the probabilistic model checker MRMC
Performance Evaluation
Model-based analysis of a protocol for reliable communication in railway worksites
Proceedings of the 15th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
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Models used for the analysis of dependability and performanceattributes of communication protocols often abstractconsiderably from the details of the actual protocol. Thesemodels often consist of concurrent sub-models and this maymake it hard to judge whether their behaviour is faithfullyreflecting the protocol. In this paper, we show how modelchecking of continuous-time Markov chains, generated fromhigh-level specifications, facilitates the analysis of both correctnessand dependability attributes. We illustrate this byrevisiting a dependability analysis [Analysis and estimation of the quality of service of group communication protocols] of a variant of thecentral access protocol of the IEEE 802.11 standard forwireless local area networks. This variant has been developedto support real-time group communication betweenautonomous mobile stations. Correctness and dependabilityproperties are formally characterised using ContinuousStochastic Logic and are automatically verified by theETMCC model checker. The models used are specified asStochastic Activity Nets.