G/G/1 queue
Template:Short description In queueing theory, a discipline within the mathematical theory of probability, the G/G/1 queue represents the queue length in a system with a single server where interarrival times have a general (meaning arbitrary) distribution and service times have a (different) general distribution.[1] The evolution of the queue can be described by the Lindley equation.[2]
The system is described in Kendall's notation where the G denotes a general distribution for both interarrival times and service times and the 1 that the model has a single server.[3][4] Different interarrival and service times are considered to be independent, and sometimes the model is denoted GI/GI/1 to emphasise this. The numerical solution for the GI/G/1 can be obtained by discretizing the time.[5]
Waiting time
Kingman's formula gives an approximation for the mean waiting time in a G/G/1 queue.[6] Lindley's integral equation is a relationship satisfied by the stationary waiting time distribution which can be solved using the Wiener–Hopf method.[7]
Multiple servers
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]Template:Rp[9] or approximating distributions by phase type distributions and then using matrix analytic methods to solve the approximate systems.[8]Template:Rp
In a G/G/2 queue with heavy-tailed job sizes, the tail of the delay time distribution is known to behave like the tail of an exponential distribution squared under low loads and like the tail of an exponential distribution for high loads.[10][11][12]
References
Page Template:Reflist/styles.css has no content.
- ^ Page Module:Citation/CS1/styles.css has no content.Bhat, U. N. (2008). "The General Queue G/G/1 and Approximations". An Introduction to Queueing Theory. pp. 169–183. doi:10.1007/978-0-8176-4725-4_9. ISBN 978-0-8176-4724-7.
- ^ Page Module:Citation/CS1/styles.css has no content.Foss, S. (2011). "The G/G/1 Queue". Wiley Encyclopedia of Operations Research and Management Science. doi:10.1002/9780470400531.eorms0878. ISBN 9780470400531.
- ^ Page Module:Citation/CS1/styles.css has no content.Kendall, D. G. (1953). "Stochastic Processes Occurring in the Theory of Queues and their Analysis by the Method of the Imbedded Markov Chain". The Annals of Mathematical Statistics. 24 (3): 338. doi:10.1214/aoms/1177728975. JSTOR 2236285.
- ^ Page Module:Citation/CS1/styles.css has no content.Smith, W. L. (1953). "On the distribution of queueing times". Mathematical Proceedings of the Cambridge Philosophical Society. 49 (3): 449. Bibcode:1953PCPS...49..449S. doi:10.1017/S0305004100028620.
- ^ Page Module:Citation/CS1/styles.css has no content.Grassmann, Winfried; Tavakoli, Javad (June 2019). "The Distribution of the Line Length in a Discrete Time GI/G/1 Queue". Performance Evaluation. 131: 43–53.
- ^ Page Module:Citation/CS1/styles.css has no content.Kingman, J. F. C. (October 1961). "The single server queue in heavy traffic". Mathematical Proceedings of the Cambridge Philosophical Society. 57 (4): 902. Bibcode:1961PCPS...57..902K. doi:10.1017/S0305004100036094. JSTOR 2984229.
- ^ Page Module:Citation/CS1/styles.css has no content.Prabhu, N. U. (1974). "Wiener-Hopf Techniques in Queueing Theory". Mathematical Methods in Queueing Theory. Lecture Notes in Economics and Mathematical Systems. Vol. 98. pp. 81–90. doi:10.1007/978-3-642-80838-8_5. ISBN 978-3-540-06763-4.
- ^ a b Page Module:Citation/CS1/styles.css has no content.Gautam, Natarajan (2012). Analysis of Queues: Methods and Applications. CRC Press. ISBN 9781439806586.
- ^ Page Module:Citation/CS1/styles.css has no content.Whitt, W. (2009). "Approximations for the GI/G/m Queue" (PDF). Production and Operations Management. 2 (2): 114–161. doi:10.1111/j.1937-5956.1993.tb00094.x.
- ^ Page Module:Citation/CS1/styles.css has no content.Harchol-Balter, M. (2012). "Task Assignment Policies for Server Farms". Performance Modeling and Design of Computer Systems. p. 408. doi:10.1017/CBO9781139226424.031. ISBN 9781139226424.
- ^ Page Module:Citation/CS1/styles.css has no content.Whitt, W. (2000). "The impact of a heavy-tailed service-time distribution upon the M/GI/s waiting-time distribution" (PDF). Queueing Systems. 36: 71–87. doi:10.1023/A:1019143505968.
- ^ Page Module:Citation/CS1/styles.css has no content.Foss, S.; Korshunov, D. (2006). "Heavy Tails in Multi-Server Queue". Queueing Systems. 52: 31. arXiv:1303.4705. doi:10.1007/s11134-006-3613-z.
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