Polarized light microscopy: Difference between revisions

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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.<ref>{{cite book
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| author = Bjarne E. Helvik
| title = Dependable Computing Systems and Communication Networks
| quote =
| publisher = Gnist Tapir
| year = 2007
| pages =
| url =
| doi =
}}</ref>
[[File:Dep-state-model.png|thumb|A simple state model with two states]]
 
It consists of creating a [[finite state machine]] which represent the different
states a system may be in. Transitions between states happen as a result of events from underlying Poisson processes with different intensities.
 
== Example ==
 
[[File:Dep-state-model-example.png|thumb|Example FSM with two working states and one failed]]
 
A redundant computer system consist of identical two compute nodes, which each
fail with an intensity of <math>\lambda</math>. When failed, they are repaired one
at the time by a single repairman with negative exponential distributed
repair times with expection <math>\mu^{-1}</math>.
 
* state 0: 0 failed units, normal state of the system.
* state 1: 1 failed unit, system operational.
* state 2: 2 failed units. system not operational.
 
Intensities from state 0 and state 1 are <math>2\lambda</math>, since each
compute node has a failure intensity of <math>\lambda</math>. Intensity from
state 1 to state 2 is <math>\lambda</math>.
Transitions from state 2 to state 1 and state 1 to state 0 represents
the repairs of the compute nodes and have the intensity <math>\mu</math> since only a single unit is repaired at the time.
 
=== Availability ===
 
The asymptotic [[availability]], i.e. availability over a long time
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.
 
: <math>\mathbf{A_0} = \begin{bmatrix}
0 & -\mu & 0 \\
-\lambda & 0 & -\mu \\
0 & \lambda & 0
\end{bmatrix}.</math>
 
The identities cells balance the sum of their column to 0:
 
: <math>\mathbf{A_1} = \begin{bmatrix}
(\lambda) & -\mu & 0 \\
-\lambda & (\lambda+\mu) & -\mu \\
0 & -\lambda & (\mu) \\
\end{bmatrix}.</math>
 
In addition the equality clause must be taken into account:
 
:<math> \sum_n  P_n = 1.</math>
 
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.
 
=== Reliability ===
 
The reliability of the system is found by making the failure states absorbing, i.e. remove all outgoing state transitions.
 
For this system the function is:
 
: <math>
R(t) = e^{-\lambda t} \,
</math>
 
== Criticism ==
 
Finite state models of systems are subject to [[State explosion problem|state explosion]]. To create
a 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.
 
== References ==
<references/>
 
[[Category:Reliability engineering]]
[[Category:Markov models]]
[[Category:Graphical models]]

Latest revision as of 16:42, 3 June 2014

Im Ima and was born on 22 September 1988. My hobbies are Golfing and Auto racing.

Also visit my webpage Women mountain bike sizing.