A stochastic approximation approach to active queue management

Shalabh Bhatnagar (), Sanjeev Patel () and Karmeshu ()
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Shalabh Bhatnagar: Indian Institute of Science
Sanjeev Patel: Jawaharlal Nehru University
Karmeshu: Jawaharlal Nehru University

Telecommunication Systems: Modelling, Analysis, Design and Management, 2018, vol. 68, issue 1, No 7, 89-104

Abstract: 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.

Keywords: Active queue management (AQM); Stochastic approximation; Dropping probability; Heavy traffic conditions; Stochastic simulation; Traffic control (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11235-017-0377-1

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