Abstract
Markov-reward models, as extensions of continuous-time Markov chains, have received increased attention for the specification and evaluation of performance and dependability properties of systems. Until now, however, the specification of reward-based performance and dependability measures has been done manually and informally. In this paper, we change this undesirable situation by the introduction of a continuous-time, reward-based stochastic logic. We argue that this logic is adequate for expressing performability measures of a large variety. We isolate two important sub-logics, the logic CSL [#!ASS+96!#,#!BKH99!#], and the novel logic CRL that allows one to express reward-based properties. These logics turn out to be complementary, which is formally established in our main duality theorem. This result implies that reward-based properties expressed in CRL for a particular Markov reward model can be interpreted as CSL properties over a derived continuo us-time Markov chain, so that model checking procedures for CSL [#!BKH99!#,#!BHHK00!#] can be employed.
Original language | English |
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Publisher | Springer |
Number of pages | 13 |
Place of Publication | Berlin |
ISBN (Print) | 978-3-540-67715-4 |
DOIs | |
Publication status | Published - Jul 2000 |
Externally published | Yes |
Keywords
- FMT-FMPA: FORMAL METHODS FOR PERFORMANCE ANALYSIS
- FMT-MC: MODEL CHECKING
- METIS-119647
- IR-19124
- EWI-7915
- FMT-PM: PROBABILISTIC METHODS