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A stochastic approximation approach to active queue management

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Abstract

Recently, a dynamic adaptive queue management with random dropping (AQMRD) scheme has been developed to capture the time-dependent variation of average queue size by incorporating the rate of change of average queue size as a parameter. A major issue with AQMRD is the choice of parameters. In this paper, a novel online stochastic approximation based optimization scheme is proposed to dynamically tune the parameters of AQMRD and which is also applicable for other active queue management (AQM) algorithms. Our optimization scheme significantly improves the throughput, average queue size, and loss-rate in relation to other AQM schemes.

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Authors and Affiliations

  1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore, 560012, India

    Shalabh Bhatnagar

  2. The School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Sanjeev Patel &  Karmeshu

Authors
  1. Shalabh Bhatnagar
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  2. Sanjeev Patel
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  3. Karmeshu
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Correspondence to Shalabh Bhatnagar.

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Bhatnagar, S., Patel, S. & Karmeshu A stochastic approximation approach to active queue management. Telecommun Syst 68, 89–104 (2018). https://doi.org/10.1007/s11235-017-0377-1

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  • DOI: https://doi.org/10.1007/s11235-017-0377-1

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