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31 relations: Arrival theorem, Expected value, Exponential distribution, Generalized foreground-background, Hard disk drive, Independence (probability theory), Johns Hopkins University Press, Kendall's notation, Laplace–Stieltjes transform, M/G/k queue, M/M/1 queue, Markov chain, Matematicheskii Sbornik, Matrix analytic method, Mean sojourn time, Method of supplementary variables, Poisson point process, Pollaczek–Khinchine formula, Probability density function, Probability distribution, Probability theory, Probability-generating function, Processor sharing, Queueing theory, Random variable, Shortest job next, Shortest remaining time, Stack (abstract data type), State space, Stationary process, Stochastic matrix.
Arrival theorem
In queueing theory, a discipline within the mathematical theory of probability, the arrival theorem (also referred to as the random observer property, ROP or job observer property) states that "upon arrival at a station, a job observes the system as if in steady state at an arbitrary instant for the system without that job." The arrival theorem always holds in open product-form networks with unbounded queues at each node, but it also holds in more general networks.
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Expected value
In probability theory, the expected value of a random variable, intuitively, is the long-run average value of repetitions of the experiment it represents.
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Exponential distribution
No description.
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Generalized foreground-background
Generalized Foreground-Background (FB), also known as Least Attained Service (LAS) is a scheduling policy.
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Hard disk drive
A hard disk drive (HDD), hard disk, hard drive or fixed disk is an electromechanical data storage device that uses magnetic storage to store and retrieve digital information using one or more rigid rapidly rotating disks (platters) coated with magnetic material.
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Independence (probability theory)
In probability theory, two events are independent, statistically independent, or stochastically independent if the occurrence of one does not affect the probability of occurrence of the other.
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Johns Hopkins University Press
The Johns Hopkins University Press (also referred to as JHU Press or JHUP) is the publishing division of Johns Hopkins University.
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Kendall's notation
In queueing theory, a discipline within the mathematical theory of probability, Kendall's notation (or sometimes Kendall notation) is the standard system used to describe and classify a queueing node.
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Laplace–Stieltjes transform
The Laplace–Stieltjes transform, named for Pierre-Simon Laplace and Thomas Joannes Stieltjes, is an integral transform similar to the Laplace transform.
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M/G/k queue
In queueing theory, a discipline within the mathematical theory of probability, an M/G/k queue is a queue model where arrivals are Markovian (modulated by a Poisson process), service times have a General distribution and there are k servers.
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M/M/1 queue
In queueing theory, a discipline within the mathematical theory of probability, an M/M/1 queue represents the queue length in a system having a single server, where arrivals are determined by a Poisson process and job service times have an exponential distribution.
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Markov chain
A Markov chain is "a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event".
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Matematicheskii Sbornik
Matematicheskii Sbornik (Математический сборник, abbreviated Mat. Sb.) is a peer reviewed Russian mathematical journal founded by the Moscow Mathematical Society in 1866.
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Matrix analytic method
In probability theory, the matrix analytic method is a technique to compute the stationary probability distribution of a Markov chain which has a repeating structure (after some point) and a state space which grows unboundedly in no more than one dimension.
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Mean sojourn time
The mean sojourn time (or sometimes mean waiting time) for an object in a system is the amount of time an object is expected to spend in a system before leaving the system for good.
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Method of supplementary variables
In queueing theory, the method of supplementary variables is a technique to solve for the stationary distribution of an M/G/1 queue.
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Poisson point process
In probability, statistics and related fields, a Poisson point process or Poisson process (also called a Poisson random measure, Poisson random point field or Poisson point field) is a type of random mathematical object that consists of points randomly located on a mathematical space.
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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).
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Probability density function
In probability theory, a probability density function (PDF), or density of a continuous random variable, is a function, whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the random variable would equal that sample.
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Probability distribution
In probability theory and statistics, a probability distribution is a mathematical function that provides the probabilities of occurrence of different possible outcomes in an experiment.
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Probability theory
Probability theory is the branch of mathematics concerned with probability.
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Probability-generating function
In probability theory, the probability generating function of a discrete random variable is a power series representation (the generating function) of the probability mass function of the random variable.
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Processor sharing
Processor sharing or egalitarian processor sharing is a service policy where the customers, clients or jobs are all served simultaneously, each receiving an equal fraction of the service capacity available.
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Queueing theory
Queueing theory is the mathematical study of waiting lines, or queues.
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Random variable
In probability and statistics, a random variable, random quantity, aleatory variable, or stochastic variable is a variable whose possible values are outcomes of a random phenomenon.
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Shortest job next
Shortest job next (SJN), also known as shortest job first (SJF) or shortest process next (SPN), is a scheduling policy that selects for execution the waiting process with the smallest execution time.
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Shortest remaining time
Shortest remaining time, also known as shortest remaining time first (SRTF), is a scheduling method that is a preemptive version of shortest job next scheduling.
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Stack (abstract data type)
In computer science, a stack is an abstract data type that serves as a collection of elements, with two principal operations.
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State space
In the theory of discrete dynamical systems, a state space is the set of all possible configurations of a system.
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Stationary process
In mathematics and statistics, a stationary process (a strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose unconditional joint probability distribution does not change when shifted in time.
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Stochastic matrix
In mathematics, a stochastic matrix (also termed probability matrix, transition matrix, substitution matrix, or Markov matrix) is a square matrix used to describe the transitions of a Markov chain.
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M/G/1, M/G/1 model, M/G/1 type Markov chain, M/G/c.
References
[1] https://en.wikipedia.org/wiki/M/G/1_queue
