IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v198y2012i1p25-5610.1007-s10479-011-0921-4.html
   My bibliography  Save this article

Polling models with multi-phase gated service

Author

Listed:
  • R. Mei
  • A. Roubos

Abstract

In this paper we introduce and analyze a new class of service policies called multi-phase gated service. This policy is a generalization of the classical single-phase and two-phase gated policies and works as follows. Each customer that arrives at queue i will have to wait K i ≥1 cycles before it receives service. The aim of this policy is to provide an interleaving scheme to avoid monopolization of the system by heavily loaded queues, by choosing the proper values of interleaving levels K i . In this paper, we analyze the effectiveness of the interleaving scheme on the queueing behavior of the system, and consider the problem of identifying the proper combination of interleaving levels ${\underline{K}}^{*}=(K_{1}^{*},\ldots,K_{N}^{*})$ that minimizes a weighted sum of the mean waiting times at each of the N queues. Obviously, the proper choice of the interleaving levels is most critical when the system is heavily loaded. For this reason, we explore the framework developed in Queueing Syst. 57, 29–46 ( 2007 ) to obtain closed-form expressions for the asymptotic waiting-time distributions in heavy traffic, and use these expressions to derive simple heuristics for approximating the optimal interleaving scheme ${\underline{K}}^{*}$ . Numerical results with simulations demonstrate that the accuracy of these approximations is extremely high. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • R. Mei & A. Roubos, 2012. "Polling models with multi-phase gated service," Annals of Operations Research, Springer, vol. 198(1), pages 25-56, September.
  • Handle: RePEc:spr:annopr:v:198:y:2012:i:1:p:25-56:10.1007/s10479-011-0921-4
    DOI: 10.1007/s10479-011-0921-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-011-0921-4
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10479-011-0921-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. E. G. Coffman & A. A. Puhalskii & M. I. Reiman, 1998. "Polling Systems in Heavy Traffic: A Bessel Process Limit," Mathematics of Operations Research, INFORMS, vol. 23(2), pages 257-304, May.
    2. Blanc, J.P.C. & van der Mei, R.D., 1992. "Optimization of polling systems with Bernoulli schedules," Research Memorandum FEW 563, Tilburg University, School of Economics and Management.
    3. S. C. Borst & O. J. Boxma, 1997. "Polling Models With and Without Switchover Times," Operations Research, INFORMS, vol. 45(4), pages 536-543, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vladimir Vishnevsky & Olga Semenova, 2021. "Polling Systems and Their Application to Telecommunication Networks," Mathematics, MDPI, vol. 9(2), pages 1-30, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sem Borst & Onno Boxma, 2018. "Polling: past, present, and perspective," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(3), pages 335-369, October.
    2. Chenxu Li, 2016. "Bessel Processes, Stochastic Volatility, And Timer Options," Mathematical Finance, Wiley Blackwell, vol. 26(1), pages 122-148, January.
    3. Ioannis Dimitriou, 2016. "Queueing analysis of the DRX power saving mechanism in fault-tolerant 3GPP LTE wireless networks," Annals of Operations Research, Springer, vol. 239(2), pages 521-552, April.
    4. David M. Markowitz & Martin I. Reiman & Lawrence M. Wein, 2000. "The Stochastic Economic Lot Scheduling Problem: Heavy Traffic Analysis of Dynamic Cyclic Policies," Operations Research, INFORMS, vol. 48(1), pages 136-154, February.
    5. Zsolt Saffer & Sergey Andreev & Yevgeni Koucheryavy, 2016. "$$M/D^{[y]}/1$$ M / D [ y ] / 1 Periodically gated vacation model and its application to IEEE 802.16 network," Annals of Operations Research, Springer, vol. 239(2), pages 497-520, April.
    6. Martin I. Reiman & Lawrence M. Wein, 1998. "Dynamic Scheduling of a Two-Class Queue with Setups," Operations Research, INFORMS, vol. 46(4), pages 532-547, August.
    7. Noah Gans & Garrett van Ryzin, 1999. "Dynamic Vehicle Dispatching: Optimal Heavy Traffic Performance and Practical Insights," Operations Research, INFORMS, vol. 47(5), pages 675-692, October.
    8. Blanc, J.P.C., 1993. "Performance Analysis and Optimization with the Power-Series Algorithm," Other publications TiSEM a1a4fc9c-dcb5-4679-9ef1-e, Tilburg University, School of Economics and Management.
    9. David M. Markowitz & Lawrence M. Wein, 2001. "Heavy Traffic Analysis of Dynamic Cyclic Policies: A Unified Treatment of the Single Machine Scheduling Problem," Operations Research, INFORMS, vol. 49(2), pages 246-270, April.
    10. Blanc, J.P.C., 1996. "Optimization of Periodic Polling Systems with Non-Preemptive, Time-Limited Service," Discussion Paper 1996-63, Tilburg University, Center for Economic Research.
    11. Otis B. Jennings, 2008. "Heavy-Traffic Limits of Queueing Networks with Polling Stations: Brownian Motion in a Wedge," Mathematics of Operations Research, INFORMS, vol. 33(1), pages 12-35, February.
    12. Kevin Granville & Steve Drekic, 2020. "A 2-class maintenance model with dynamic server behavior," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 34-96, April.
    13. Otis B. Jennings, 2010. "Averaging Principles for a Diffusion-Scaled, Heavy-Traffic Polling Station with K Job Classes," Mathematics of Operations Research, INFORMS, vol. 35(3), pages 669-703, August.
    14. Dieter Fiems, 2024. "Performance of a Synchronisation Station with Abandonment," Mathematics, MDPI, vol. 12(5), pages 1-12, February.
    15. Blanc, J.P.C. & van der Mei, R.D., 1993. "The power-series algorithm applied to polling systems with a dormant server," Other publications TiSEM ab862d96-146f-419e-a56e-2, Tilburg University, School of Economics and Management.
    16. Dieter Fiems & Tuan Phung-Duc, 2019. "Light-traffic analysis of random access systems without collisions," Annals of Operations Research, Springer, vol. 277(2), pages 311-327, June.
    17. Martin I. Reiman & Lawrence M. Wein, 1999. "Heavy Traffic Analysis of Polling Systems in Tandem," Operations Research, INFORMS, vol. 47(4), pages 524-534, August.
    18. Ibragimov, Rustam & Phillips, Peter C.B., 2008. "Regression Asymptotics Using Martingale Convergence Methods," Econometric Theory, Cambridge University Press, vol. 24(4), pages 888-947, August.
    19. Marko A. A. Boon & Onno J. Boxma & Offer Kella & Masakiyo Miyazawa, 2017. "Queue-length balance equations in multiclass multiserver queues and their generalizations," Queueing Systems: Theory and Applications, Springer, vol. 86(3), pages 277-299, August.
    20. Rosario Delgado, 2016. "A two-queue polling model with priority on one queue and heavy-tailed On/Off sources: a heavy-traffic limit," Queueing Systems: Theory and Applications, Springer, vol. 83(1), pages 57-85, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:198:y:2012:i:1:p:25-56:10.1007/s10479-011-0921-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.