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Dynamic service rate control for a single‐server queue with Markov‐modulated arrivals

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  • Ravi Kumar
  • Mark E. Lewis
  • Huseyin Topaloglu

Abstract

We consider the problem of service rate control of a single‐server queueing system with a finite‐state Markov‐modulated Poisson arrival process. We show that the optimal service rate is nondecreasing in the number of customers in the system; higher congestion levels warrant higher service rates. On the contrary, however, we show that the optimal service rate is not necessarily monotone in the current arrival rate. If the modulating process satisfies a stochastic monotonicity property, the monotonicity is recovered. We examine several heuristics and show where heuristics are reasonable substitutes for the optimal control. None of the heuristics perform well in all the regimes and the fluctuation rate of the modulating process plays an important role in deciding the right heuristic. Second, we discuss when the Markov‐modulated Poisson process with service rate control can act as a heuristic itself to approximate the control of a system with a periodic nonhomogeneous Poisson arrival process. Not only is the current model of interest in the control of Internet or mobile networks with bursty traffic, but it is also useful in providing a tractable alternative for the control of service centers with nonstationary arrival rates. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 661–677, 2013

Suggested Citation

  • Ravi Kumar & Mark E. Lewis & Huseyin Topaloglu, 2013. "Dynamic service rate control for a single‐server queue with Markov‐modulated arrivals," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(8), pages 661-677, December.
    • Handle: RePEc:wly:navres:v:60:y:2013:i:8:p:661-677
    DOI: 10.1002/nav.21560
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    References listed on IDEAS

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    Cited by:

    1. Legros, Benjamin, 2022. "The principal-agent problem for service rate event-dependency," European Journal of Operational Research, Elsevier, vol. 297(3), pages 949-963.
    2. Huanan Zhang & Cong Shi & Chao Qin & Cheng Hua, 2016. "Stochastic regret minimization for revenue management problems with nonstationary demands," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(6), pages 433-448, September.
    3. Guodong Pang & Andrey Sarantsev & Yana Belopolskaya & Yuri Suhov, 2020. "Stationary distributions and convergence for M/M/1 queues in interactive random environment," Queueing Systems: Theory and Applications, Springer, vol. 94(3), pages 357-392, April.
    4. Benjamin Legros, 2022. "The principal-agent problem for service rate event-dependency," Post-Print hal-03605421, HAL.
    5. Shing Chih Tsai & Jun Luo & Chi Ching Sung, 2017. "Combined variance reduction techniques in fully sequential selection procedures," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(6), pages 502-527, September.

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