Queueing - ² G for General distribution(GI ± When the...

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Queueing Theory ± A very basic introduction to queueing theory. ± Queueing theory is a very complicated topic, here we will deal with the fundamentals only Server Queueing Theory ± An arrival requests, a server to process/serve them, and a queue for arrivals that arrive while the server is busy ± Examples …. ± Usually, defined as A/B/c/K ² A is the interarrival time distribution ² B is the service time distribution ² c is the number of servers ² K is the system capacity (queue + being served) Queueing Theory ± For A and B, we usually use ² M for exponential distribution ² D for deterministic distribution
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Unformatted text preview: ² G for General distribution (GI) ± When the system capacity is infinite, we use A/B/c ± The simplest queue is M/M/1 ± Examples … Queueing Theory ± λ is the arrival rate (arrival per second) ± 1/ λ is the interarrival time ± If the arrival is Poisson, the interarrival is exponential ± μ is the service rate, 1/ μ is the service time. ± The traffic intensity (occupancy) is defined as ρ = λ / μ Queueing Theory time Number of customers Queueing Theory T N T N total λ μ ρ = − = − = = 1 1...
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Queueing - ² G for General distribution(GI ± When the...

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