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"Measurements are not to provide numbers but to provide insight" – Ingrid Bucher
"…all models are approximations. Essentially, all models are wrong, but some are useful. However, the approximate nature of the model must always be borne in mind… " - George Box.
Lecture outline: What are common multi-server queueing systems? how can they be analyzed?
1. M/M/infinity infinite server delay centers
State probability distribution
Performance measures of M/M/infinity
2. M/M/c multiserver queueing centers
State probability distribution
Benefit of multi-server queue
Queueing probability
Comparing alternatives (M/M/1 vs. M/M/2)
3. M/M/c/k finite buffer queue
M/M/c/c loss systems
Erlang B formula for calculating blocking probability
M/M/1/k (M/M/1 queue with k number of finite buffers)
State probability distribution
Blocking probability
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