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An M/M/∞ queue is a stochastic process whose state space is the set {0,1,2,3,...} where the value corresponds to the number of customers currently being served. Since, the number of servers in parallel is infinite, there is no queue and the number of customers in the systems coincides with the number of customers being served at any moment.
In queueing theory, a discipline within the mathematical theory of probability, the M/M/c queue (or Erlang–C model [1]: 495 ) is a multi-server queueing model. [2] In Kendall's notation it describes a system where arrivals form a single queue and are governed by a Poisson process, there are c servers, and job service times are exponentially distributed. [3]
In 1953, David George Kendall solved the GI/M/k queue [15] and introduced the modern notation for queues, now known as Kendall's notation. In 1957, Pollaczek studied the GI/G/1 using an integral equation. [16] John Kingman gave a formula for the mean waiting time in a G/G/1 queue, now known as Kingman's formula. [17]
M X /M Y /1 queue: D: Degenerate distribution: A deterministic or fixed service time. M/D/1 queue: E k: Erlang distribution: An Erlang distribution with k as the shape parameter (i.e., sum of k i.i.d. exponential random variables). G: General distribution: Although G usually refers to independent service time, some authors prefer to use GI to ...
The Queuing Rule of Thumb (QROT) is a mathematical formula known as the queuing constraint equation when it is used to find an approximation of servers required to service a queue. The formula is written as an inequality relating the number of servers (s), total number of service requestors (N), service time (r), and the maximum time to empty ...
The theorem can be generalised for "only a few cases," but remains valid for M/M/c queues and Geom/Geom/1 queues. [7]It is thought that Burke's theorem does not extend to queues fed by a Markovian arrival processes (MAP) and is conjectured that the output process of an MAP/M/1 queue is an MAP only if the queue is an M/M/1 queue.
An M/M/1 queue is a stochastic process whose state space is the set {0,1,2,3,...} where the value corresponds to the number of customers in the system, including any currently in service. Arrivals occur at rate λ according to a Poisson process and move the process from state i to i + 1.
The Erlang B formula (or Erlang-B with a hyphen), also known as the Erlang loss formula, is a formula for the blocking probability that describes the probability of call losses for a group of identical parallel resources (telephone lines, circuits, traffic channels, or equivalent), sometimes referred to as an M/M/c/c queue. [5]