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  2. M/G/1 queue - Wikipedia

    en.wikipedia.org/wiki/M/G/1_queue

    The Pollaczek–Khinchine formula gives the mean queue length and mean waiting time in the system. [ 9 ] [ 10 ] Recently, the Pollaczek–Khinchine formula has been extended to the case of infinite service moments, thanks to the use of Robinson's Non-Standard Analysis.

  3. Kendall's notation - Wikipedia

    en.wikipedia.org/wiki/Kendall's_notation

    A M/M/1 queue means that the time between arrivals is Markovian (M), i.e. the inter-arrival time follows an exponential distribution of parameter λ. The second M means that the service time is Markovian: it follows an exponential distribution of parameter μ. The last parameter is the number of service channel which one (1).

  4. Lindley equation - Wikipedia

    en.wikipedia.org/wiki/Lindley_equation

    Lindley's integral equation is a relationship satisfied by the stationary waiting time distribution F(x) in a G/G/1 queue. = ()Where K(x) is the distribution function of the random variable denoting the difference between the (k - 1)th customer's arrival and the inter-arrival time between (k - 1)th and kth customers.

  5. M/M/1 queue - Wikipedia

    en.wikipedia.org/wiki/M/M/1_queue

    Service times have an exponential distribution with rate parameter μ in the M/M/1 queue, where 1/μ is the mean service time. All arrival times and services times are (usually) assumed to be independent of one another. [2] A single server serves customers one at a time from the front of the queue, according to a first-come, first-served ...

  6. Markovian arrival process - Wikipedia

    en.wikipedia.org/wiki/Markovian_arrival_process

    In queueing theory, a discipline within the mathematical theory of probability, a Markovian arrival process (MAP or MArP [1]) is a mathematical model for the time between job arrivals to a system. The simplest such process is a Poisson process where the time between each arrival is exponentially distributed. [2] [3]

  7. G/G/1 queue - Wikipedia

    en.wikipedia.org/wiki/G/G/1_queue

    Few results are known for the general G/G/k model as it generalises the M/G/k queue for which few metrics are known. Bounds can be computed using mean value analysis techniques, adapting results from the M/M/c queue model, using heavy traffic approximations, empirical results [8]: 189 [9] or approximating distributions by phase type distributions and then using matrix analytic methods to solve ...

  8. Discrete-event simulation - Wikipedia

    en.wikipedia.org/wiki/Discrete-event_simulation

    Each event occurs at a particular instant in time and marks a change of state in the system. [1] Between consecutive events, no change in the system is assumed to occur; thus the simulation time can directly jump to the occurrence time of the next event, which is called next-event time progression.

  9. Pollaczek–Khinchine formula - Wikipedia

    en.wikipedia.org/wiki/Pollaczek–Khinchine_formula

    In queueing theory, a discipline within the mathematical theory of probability, the Pollaczek–Khinchine formula states a relationship between the queue length and service time distribution Laplace transforms for an M/G/1 queue (where jobs arrive according to a Poisson process and have general service time distribution). The term is also used ...