Queuing theory is indispensable, but here is an introduction to the simplest queuing model - an M/M/1 queue. Also included is the discussion on Poisson process, which is the underlying assumption for the M/M/1 queue.
Second channel video on variance of Poisson distribution:
To me, this is mainly a “prequel“ which serves as a prerequisite for the next video, even though the next video is not as long.
For the files created for this video, please visit and enter the password:
queuingmodelM/M/1
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Sources:
Different queues:
M/M/1 queue:
M/M/c queue:
M/M/∞ queue: ∞_queue
M/G/1 queue:
M/G/k queue:
G/M/1 queue:
G/G/1 queue:
Jackson Network:
More general queues: ’s_notation
The (transient) solution: Computer Networks and Systems. New York, NY: Springer New York. p. 72 (uses moment-generating function and Laplace transforms); for more details, see Gross, D. and Harris, C.M., Fundamentals of Queueing Theory, Wiley, New York, 1974, 1985. (Section )
Other related sources:
Markov Chains: ~james/Markov/
Birth-and-death chain: –death_process
Bessel functions (for the solution to the differential equations): #Modified_Bessel_functions_:_Iα,_Kα
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