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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).
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 ...
and F(u) is the service time distribution and λ the Poisson arrival rate of jobs to the queue. Markov chains with generator matrices or block matrices of this form are called M/G/1 type Markov chains, [ 13 ] a term coined by Marcel F. Neuts .
The arrivals in the process whose intensity is () are the "daughters" of the arrival at time . The integral ∫ 0 ∞ ϕ ( t ) d t {\displaystyle \int _{0}^{\infty }\phi (t)\,dt} is the average number of daughters of each arrival and is called the branching ratio .
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.
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.
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]
In queueing theory, a discipline within the mathematical theory of probability, a rational arrival process (RAP) is a mathematical model for the time between job arrivals to a system. It extends the concept of a Markov arrival process , allowing for dependent matrix-exponential distributed inter-arrival times.