How to solve the markov transition matrix

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SUMMARY

The discussion focuses on solving a Markov transition matrix to determine the availability of a node dependent on network status. The matrix includes states for node and network availability, with repair rates (R1, R2) and failure rates (F1, F2) defined. The participant attempts to solve the equations symbolically and using MATLAB, but encounters issues with redundancy in the equations. A solution is provided, indicating that retaining three of the four equations along with the normalization condition leads to a unique solution for the probabilities.

PREREQUISITES
  • Understanding of Markov models and transition matrices
  • Familiarity with probability theory and normalization conditions
  • Proficiency in MATLAB for solving linear systems
  • Knowledge of repair and failure rates in network systems
NEXT STEPS
  • Study how to derive probabilities from Markov transition matrices
  • Learn to implement linear algebra techniques in MATLAB for system solving
  • Explore redundancy in linear equations and methods to simplify systems
  • Investigate real-world applications of Markov models in network reliability
USEFUL FOR

Students and professionals in network engineering, operations research, and applied mathematics who are working with Markov models and need to analyze system availability and reliability.

allamar2012
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Homework Statement


I design a markov model to study the availability of a node which will not work unless the network work: I make the following matrix. In which (i,j) means i is node up /down and j is network up/down. R1,R2 means the repair rate for node and network. F1,F2 means the failure rate for node and network.
(0,0) (1,0) (0,1) (1,1)
(0,0) 0 R1 R2 0
(1,0) F1 0 0 R2
(0,1) F2 0 0 R1
(1,1) 0 F2 F1 0

Homework Equations



I do the following equations to detemine the P(1,1)
(R1+R2)P(0,0)= F1 P(1,0) + F2 P(0,1)
(F1+R2)P(1,0) = R1 P(0,0) +F1 P(1,1)
(F2+R1)P(0,1) = R2 P(0,0) +F1 P(1,1)
(F2+F1)P(1,1) = R2 P(1,0) +R1 P(0,1)

P(0,0) + P(1,0) + P(0,1) + P(1,1) = 1

I do this symbolically in which it gives me long recursive and I couldn't complete it.

The Attempt at a Solution


is my equation right or wrong?
I need advise in how to solve this equations to get P(1,1).
I try MATLAB to calculate this equations as linear system
it gives me
[ 0
0
0
0 ]

Thanks
 
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allamar2012 said:

Homework Statement


I design a markov model to study the availability of a node which will not work unless the network work: I make the following matrix. In which (i,j) means i is node up /down and j is network up/down. R1,R2 means the repair rate for node and network. F1,F2 means the failure rate for node and network.
(0,0) (1,0) (0,1) (1,1)
(0,0) 0 R1 R2 0
(1,0) F1 0 0 R2
(0,1) F2 0 0 R1
(1,1) 0 F2 F1 0

Homework Equations



I do the following equations to detemine the P(1,1)
(R1+R2)P(0,0)= F1 P(1,0) + F2 P(0,1)
(F1+R2)P(1,0) = R1 P(0,0) +F1 P(1,1)
(F2+R1)P(0,1) = R2 P(0,0) +F1 P(1,1)
(F2+F1)P(1,1) = R2 P(1,0) +R1 P(0,1)

P(0,0) + P(1,0) + P(0,1) + P(1,1) = 1

I do this symbolically in which it gives me long recursive and I couldn't complete it.

The Attempt at a Solution


is my equation right or wrong?
I need advise in how to solve this equations to get P(1,1).
I try MATLAB to calculate this equations as linear system
it gives me
[ 0
0
0
0 ]

Thanks

The first 4 equations have a redundancy: given that any three of them hold, the 4th one also holds. So, keep any three of the first four equations, and append the normalization equation P(0,0) + ... + P(1,1) = 1. That 4x4 linear system does have a unique solution.

It is not too bad, just lengthy. You can get P(0,0) = [F1 P(1,0) + F2 P(0,1)]/(R1+R2) from the first equation. You can get P(1,1) = [R2 P(1,0) +R1 P(0,1)]/(F2+F1) from the fourth equation. Now you can substitute these expressions for P(0,0) and P(1,1) into the second (or third) equation and into the sum(P) = 1 equation to get two equations in the two unknowns P(0,1) and P(1,0). It is messy and time-consuming, but is nevertheless straightforward.

RGV
 
Hi Ray :)
Thank you very much, it's helpful.
 

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