EEL6507sp09L15
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EEL6507 Spring 2009, Lecture 15, Wednesday 2009/02/09 (Notes created by Ajay Jain)
- Finish M/M/m
- M/M/I/k Queue
State Space Representation

- Recall from previous result
and since we should have
hence,
- CASE 1: K < m-1
So, λk = λ,μk + 1 = (k + 1)μ
- CASE 2: K > m
So, λk = λ,μk + 1 = mμ
Where,
Solving Further with Pm value we get,
Let,
Then
![Prob\left[All\ Busy \right]=\frac{\frac{(m\rho)^m}{m!}\frac{1}{1-\rho}}{ \sum_{n=0}^{m-1}(m\rho)^k \frac{1}{k!}+P_0\frac{(m\rho)^m}{m!}\frac{1}{1-\rho} }](/wiki/images/math/0/3/1/031b45d9c93a73226e5271b8821e8987.png)
This is ERLANG-C Formula
M/M/1/k
From previous results
For a M / M / 1 / k system, we define the following:
Pk = 0,k < m
Normalising for finding value of P0
Let,
So
- Probability of drop
![Prob\left[Drop \right]=P_k=\frac{(\rho)^k (1-\rho)}{1-(\rho)^{k+1}}](/wiki/images/math/e/a/1/ea1048611648974211b7c96988649923.png)
