Dependability for Systems with a Partitioned State Space: Markov and Semi-Markov Theory and Computational Implementation

Front Cover
Springer New York, Aug 1, 1994 - Mathematics - 244 pages
0 Reviews
Probabilistic models of technical systems are studied here whose finite state space is partitioned into two or more subsets. The systems considered are such that each of those subsets of the state space will correspond to a certain performance level of the system. The crudest approach differentiates between 'working' and 'failed' system states only. Another, more sophisticated, approach will differentiate between the various levels of redundancy provided by the system. The dependability characteristics examined here are random variables associated with the state space's partitioned structure; some typical ones are as follows • The sequence of the lengths of the system's working periods; • The sequences of the times spent by the system at the various performance levels; • The cumulative time spent by the system in the set of working states during the first m working periods; • The total cumulative 'up' time of the system until final breakdown; • The number of repair events during a fmite time interval; • The number of repair events until final system breakdown; • Any combination of the above. These dependability characteristics will be discussed within the Markov and semi-Markov frameworks.

From inside the book

What people are saying - Write a review

We haven't found any reviews in the usual places.


Stochastic processes for dependability assessment
Sojourn times for discreteparameter Markov chains
The number of visits until absorption to subsets of the state space by

11 other sections not shown

Other editions - View all

Common terms and phrases

References to this book

All Book Search results »

Bibliographic information