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(a) Given that an arrival occurs in the interval (nδ, (n + 1)δ) for the sampled-time M/M/1 model in Figure 6.5, find the conditional PMF of the state of the system at time nδ (assume n is arbitrarily large and assume positive recurrence).
(b) For the same model, again in steady state but not conditioned on an arrival in (nδ, (n + 1)δ), find the probabilityQ(i, j) (i ≥ j > 0) that the system is in state i at nδ and that i - j departures occur before the next arrival.
(c) Find the expected number of customers seen in the system by the first arrival after time nδ. Note: The purpose of this exercise is to make you cautious about the meaning of 'the state seen by a random arrival'.
Text Book: Stochastic Processes: Theory for Applications By Robert G. Gallager.
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o This is a linear model. If your model needs a different engine, then you need to rethink your approach to the model. Remember, there are no IF, Max, or MIN statements in linear models.
Plan the analysis
State the hypotheses that you are going to test.
modelise as a markov chain
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