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The Distributional Little's Law and Its Applications

Author

Listed:
  • Dimitris Bertsimas

    (Massachusetts Institute of Technology, Cambridge, Massachusetts)

  • Daisuke Nakazato

    (Massachusetts Institute of Technology, Cambridge, Massachusetts)

Abstract

This paper discusses the distributional Little's law and examines its applications in a variety of queueing systems. The distributional law relates the steady-state distributions of the number in the system (or in the queue) and the time spent in the system (or in the queue) in a queueing system under FIFO. We provide a new proof of the distributional law and in the process we generalize a well known theorem of Burke on the equality of pre-arrival and postdeparture probabilities. More importantly, we demonstrate that the distributional law has important algorithmic and structural applications and can be used to derive various performance characteristics of several queueing systems which admit distributional laws. As a result, we believe that the distributional law is a powerful tool for the derivation of performance measures in queueing systems and can lead to a certain unification of queueing theory.

Suggested Citation

  • Dimitris Bertsimas & Daisuke Nakazato, 1995. "The Distributional Little's Law and Its Applications," Operations Research, INFORMS, vol. 43(2), pages 298-310, April.
    • Handle: RePEc:inm:oropre:v:43:y:1995:i:2:p:298-310
    DOI: 10.1287/opre.43.2.298
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    Citations

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    Cited by:

    1. Jianfu Wang & Opher Baron & Alan Scheller-Wolf, 2015. "M/M/c Queue with Two Priority Classes," Operations Research, INFORMS, vol. 63(3), pages 733-749, June.
    2. Rouba Ibrahim & Mor Armony & Achal Bassamboo, 2017. "Does the Past Predict the Future? The Case of Delay Announcements in Service Systems," Management Science, INFORMS, vol. 63(6), pages 1762-1780, June.
    3. Mor Harchol-Balter & Takayuki Osogami & Alan Scheller-Wolf & Adam Wierman, 2005. "Multi-Server Queueing Systems with Multiple Priority Classes," Queueing Systems: Theory and Applications, Springer, vol. 51(3), pages 331-360, December.
    4. Nam K. Kim & Kyung C. Chae & Mohan L. Chaudhry, 2004. "An Invariance Relation and a Unified Method to Derive Stationary Queue-Length Distributions," Operations Research, INFORMS, vol. 52(5), pages 756-764, October.
    5. Opher Baron & Oded Berman & Dmitry Krass & Jianfu Wang, 2014. "Using Strategic Idleness to Improve Customer Service Experience in Service Networks," Operations Research, INFORMS, vol. 62(1), pages 123-140, February.
    6. John D. C. Little, 2011. "OR FORUM---Little's Law as Viewed on Its 50th Anniversary," Operations Research, INFORMS, vol. 59(3), pages 536-549, June.
    7. Hossein Abouee-Mehrizi & Opher Baron & Oded Berman, 2014. "Exact Analysis of Capacitated Two-Echelon Inventory Systems with Priorities," Manufacturing & Service Operations Management, INFORMS, vol. 16(4), pages 561-577, October.
    8. George C. Mytalas & Michael A. Zazanis, 2022. "Service with a queue and a random capacity cart: random processing batches and E-limited policies," Annals of Operations Research, Springer, vol. 317(1), pages 147-178, October.
    9. Gérard Hébuterne & Catherine Rosenberg, 1999. "Arrival and departure state distributions in the general bulk‐service queue," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(1), pages 107-118, February.
    10. Hossein Abouee-Mehrizi & Opher Baron, 2016. "State-dependent M/G/1 queueing systems," Queueing Systems: Theory and Applications, Springer, vol. 82(1), pages 121-148, February.
    11. Bertsimas, Dimitris., 1995. "Transient laws of non-stationary queueing systems and their applications," Working papers 3836-95., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    12. Kristen Gardner & Rhonda Righter, 2020. "Product forms for FCFS queueing models with arbitrary server-job compatibilities: an overview," Queueing Systems: Theory and Applications, Springer, vol. 96(1), pages 3-51, October.

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