A dependability state diagram is a method for modelling a system as a Markov chain. It is used in reliability engineering for availability and reliability analysis.[1]
It consists of creating a finite state machine which represent the differentstates a system may be in. Transitions between states happen as a result of events from underlying Poisson processes with different intensities.
A redundant computer system consist of identical two-compute nodes, which each fail with an intensity of
λ
\mu-1
Intensities from state 0 and state 1 are
2λ
λ
λ
\mu
The asymptotic availability, i.e. availability over a long period, of the system is equal to the probability that the model is in state 1 or state 2.
This is calculated by making a set of linear equations of the state transition and solving the linear system.
The matrix is constructed with a row for each state. In a row, the intensity into the state is set in the column with the same index, with a negative term.
A0 |
=\begin{bmatrix} 0&-\mu&0\\ -λ&0&-\mu\\ 0&λ&0 \end{bmatrix}.
The identities cells balance the sum of their column to 0:
A1 |
=\begin{bmatrix} (λ)&-\mu&0\\ -λ&(λ+\mu)&-\mu\\ 0&-λ&(\mu)\\ \end{bmatrix}.
In addition the equality clause must be taken into account:
\sumnPn=1.
By solving this equation, the probability of being in state 1 or state 2 can be found, which is equal to the long-term availability of the service.
The reliability of the system is found by making the failure states absorbing, i.e. removing all outgoing state transitions.
For this system the function is:
R(t)=e-λ
Finite state models of systems are subject to state explosion. To createa realistic model of a system one ends up with a model with so many states that it is infeasible to solve or draw the model.