SFWRENG 4E03 Lecture Notes - Lecture 12: Mathtype, Markov Chain

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True: mva cannot get steady state distribution, but instead e[r], e[n], (cid:540), . 1 = probability that there are 0 jobs (but not more) 2nd moment of x: e[x2] = 0. 52: 0. 5 + 1. 52, 0. 5 nth moment [e[xn]]: x p x x. If the means are both different expected jobs in an m/g/1 queue. Option 1: x ~ exp(2) var(x) = 0. 25. Traffic equations (cid:540)1 = (cid:540)2 + 0. 05 (cid:540)1 (cid:540)2 = 0. 5(cid:540)1. Now that you have c, you can find your probabilities. If service times are ~exp((cid:541)), then all work conserving policies have equal e[r] Calculate variance of general distribution and leverage that for . Markovian (poisson arrivals) / markovian (exponential service time) / 4 servers / room for 4 jobs in system (cid:540) = given (cid:541) = given. 1 (cid:540) is not exact arrival rate to system. E[n] = weighted sum of being in each probability.

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