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A feedback fluid queue with two congestion control thresholds

Author

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  • R. Malhotra
  • M. Mandjes
  • W. Scheinhardt
  • J. Berg

Abstract

Feedback fluid queues play an important role in modeling congestion control mechanisms for packet networks. In this paper we present and analyze a fluid queue with a feedback-based traffic rate adaptation scheme which uses two thresholds. The higher threshold B 1 is used to signal the beginning of congestion while the lower threshold B 2 signals the end of congestion. These two parameters together allow to make the trade-off between maximizing throughput performance and minimizing delay. The difference between the two thresholds helps to control the amount of feedback signals sent to the traffic source. In our model the input source can behave like either of two Markov fluid processes. The first applies as long as the upper threshold B 1 has not been hit from below. As soon as that happens, the traffic source adapts and switches to the second process, until B 2 (smaller than B 1 ) is hit from above. We analyze the model by setting up the Kolmogorov forward equations, then solving the corresponding balance equations using a spectral expansion, and finally identifying sufficient constraints to solve for the unknowns in the solution. In particular, our analysis yields expressions for the stationary distribution of the buffer occupancy, the buffer delay distribution, and the throughput. Copyright The Author(s) 2009

Suggested Citation

  • R. Malhotra & M. Mandjes & W. Scheinhardt & J. Berg, 2009. "A feedback fluid queue with two congestion control thresholds," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 70(1), pages 149-169, August.
  • Handle: RePEc:spr:mathme:v:70:y:2009:i:1:p:149-169
    DOI: 10.1007/s00186-008-0235-8
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    Cited by:

    1. D’Auria, Bernardo & Adan, Ivo J.B.F. & Bekker, René & Kulkarni, Vidyadhar, 2022. "An M/M/c queue with queueing-time dependent service rates," European Journal of Operational Research, Elsevier, vol. 299(2), pages 566-579.
    2. O’Reilly, Małgorzata M., 2014. "Multi-stage stochastic fluid models for congestion control," European Journal of Operational Research, Elsevier, vol. 238(2), pages 514-526.

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