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In queueing theory, a discipline within the mathematical theory of probability, the M/M/∞ queue is a multi-server queueing model where every arrival experiences immediate service and does not wait. In Kendall's notation it describes a system where arrivals are governed by a Poisson process, there are infinitely many servers, so jobs do not need to wait for a server. Each job has an exponentially distributed service time. It is a limit of the M/M/c queue model where the number of servers c becomes very large.
Stochastic Petri nets are a form of Petri net where the transitions fire after a probabilistic delay determined by a random variable.
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 and a state space which grows unboundedly in no more than one dimension. Such models are often described as M/G/1 type Markov chains because they can describe transitions in an M/G/1 queue. The method is a more complicated version of the matrix geometric method and is the classical solution method for M/G/1 chains.
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.
Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behaviour of biological molecules or complexes that can adopt a large number of possible functional states.
References
- ↑ Argent-Katwala, A.; Bradley, J. T. (2006). "Functional Performance Specification with Stochastic Probes" (PDF). Formal Methods and Stochastic Models for Performance Evaluation. Lecture Notes in Computer Science. 4054. p. 31. doi:10.1007/11777830_3. ISBN 978-3-540-35362-1.
- ↑ Hayden, R. A.; Bradley, J. T.; Clark, A. (2013). "Performance Specification and Evaluation with Unified Stochastic Probes and Fluid Analysis" (PDF). IEEE Transactions on Software Engineering. 39: 97–118. CiteSeerX 10.1.1.297.5068 . doi:10.1109/TSE.2012.1.
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