Skip to main content

Advertisement

Springer Nature Link
Log in

A stochastic approximation approach to active queue management

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Floyd, S., & Jacobson, V. (1993). Random early detection gateways for congestion avoidance. IEEE/ACM Transactions on Networking, 1(4), 397–413.

    Article  Google Scholar 

  2. Athuraliya, S., Li, V. H., Low, S. H., & Elissa, Q. Y. (2002). REM: Active queue management. IEEE Network, 15(3), 48–53.

    Article  Google Scholar 

  3. Meckenney, P. E. (1990). Stochastic fair queuing. Proceedings IEEE INFOCOM, 2, 733–740.

    Google Scholar 

  4. Hollot, C. V., Misra, V., Towsley, D., Gong, W. (2001). On designing improved controllers for AQM routers supporting TCP flows. In Proceedings of the IEEE INFOCOM (pp. 1726–1734).

  5. Feng, W., Shin, K. G., Kandlur, D. D., & Saha, D. (2002). The BLUE active queue management algorithms. IEEE/ACM Transactions on Networking, 10(4), 513–528.

    Article  Google Scholar 

  6. Feng, G., Agarwal, A . K., Jayaraman, A., & Siew, C . K. (2004). Modified RED gateways under bursty traffic. IEEE Communications Letter, 8(5), 323–325.

    Article  Google Scholar 

  7. Floyd, S., Gummadi, R., Shenker, S. (2001). Adaptive RED: An algorithm for increasing the robustness of RED’s active queue management. Technical Report, UC, Berkeley, CA, (Online) http://www.icir.org/floyd/papers.html.

  8. Feng, C. W., Huang, L. F., Xu, C., & Chang, Y. C. (2017). Congestion control scheme performance analysis based on nonlinear RED. IEEE System Journal, 99, 1–8.

    Google Scholar 

  9. Verma, R., Iyer, A., & Karandikar, A. (2003). Active queue management using adaptive RED. Journal of Communications and Networks, 5(3), 275–281.

    Article  Google Scholar 

  10. Zadeh, H. Y., Habibi, A., Li, X., Jafarkhani, H., & Bauer, C. (2012). A statistical study of loss-delay tradeoff for RED queues. IEEE Transactions on Communications, 60(7), 1966–1974.

    Article  Google Scholar 

  11. Xu, Q., & Sun, J. (2012). New active queue management scheme based on statistical analysis. In Proceedings of WCICA ’12, (pp. 2562–2565). Beijing, China.

  12. Kulatungay, C., Kuhnz, N., Fairhursty, G., & Ros, D. (2015). Tackling Bufferbloat in capacity-limited networks. In EuCNC’15 (pp. 381-385). doi:10.1109/EuCNC.2015.7194103.

  13. Wang, J., Rong, L., & Liu, Y. (2008). A robust proportional controller for AQM based on optimized second-order system model. Computer Communications, 31(10), 2468–2477.

    Article  Google Scholar 

  14. Chavan, K., Kumar, R. G., Belur, M. N., & Karandikar, A. (2011). Robust active queue management for wireless networks. IEEE Transactions on Control Systems Technology, 19(6), 1630–1638.

    Article  Google Scholar 

  15. Tan, L., Zhang, W., Peng, G., & Chen, G. (2006). Stability of TCP/RED systems in AQM routers. IEEE Transactions on Automatic Control, 51(8), 1393–1398.

    Article  Google Scholar 

  16. Woo, S., & Kim, K. (2010). Tight upper bound for stability of TCP/RED systems in AQM routers. IEEE Communications Letters, 14(7), 682–684.

    Article  Google Scholar 

  17. Qazi, I. A., Andrew, L. L. H., & Znati, T. K. (2012). Congestion control with multipacket feedback. IEEE/ACM Transactions on Networking, 20(6), 1721–1733.

    Article  Google Scholar 

  18. Poojary, S., & Sharma, V. (2016). Analysis of multiple flows using different high speed TCP protocols on a general network. Performance Evaluation, 104, 4262.

    Article  Google Scholar 

  19. Akyildiz, I. F., Lee, A., Wang, P., Luo, M., & Chou, W. (2015). Research challenges for traffic engineering in software defined networks. IEEE Network, 30(3), 52–58.

    Article  Google Scholar 

  20. Akyildiz, I. F., Nie, S., Lin, S.-C., & Chandrasekaran, M. (2016). 5G roadmap: 10 key enabling technologies. Computer Networks, 106(4), 17–48.

    Article  Google Scholar 

  21. Harel, A., Namn, S., & Sturm, J. (1999). Simple bounds for closed queuing networks. Queueing Systems, 31(1), 125–135.

    Article  Google Scholar 

  22. Padhye, J., Firoiu, V., Towsley, D. F., & Kurose, J. F. (2000). Modeling TCP Reno performance: A simple model and its empirical validation. IEEE/ACM Transactions on Networking, 8, 133–145.

    Article  Google Scholar 

  23. Yan, J., Muhlbauer, W., & Plattner, B. (2011). An analytical model for streaming over TCP. In NEW2AN (pp. 370–381).

  24. Yan, J., & Plattner, B. (2013). A simple solution to find the distribution of TCP window sizes. IEEE Communications Letters, 17(2), 417–419.

    Article  Google Scholar 

  25. Gemikonakli, E., Ever, E., Mapp, G., & Gemikonaklii, O. (2017). Admission control and buffer management of wireless communication systems with mobile stations and integrated voice and data services. Telecommunication Systems, 65(4), 663–675.

    Article  Google Scholar 

  26. Salah, K., & Kafhali, S. E. (2017). Performance modeling and analysis of hypoexponential network servers. Telecommunication Systems, 65(4), 717–728.

    Article  Google Scholar 

  27. Prashanth, L. A., Bhatnagar, S., Fu, M., & Marcus, S. (2017). Adaptive system optimization using random directions stochastic approximation. IEEE Transactions on Automatic Control, 62(5), 2223–2238.

    Article  Google Scholar 

  28. Spall, J. C. (1992). Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control, 37(3), 332–341.

    Article  Google Scholar 

  29. Bhatnagar, S. (2007). Adaptive Newton-based smoothed functional algorithms for simulation optimization. ACM Transactions on Modeling and Computer Simulation, 18(1), 2:1–2:35.

    Article  Google Scholar 

  30. Karmeshu, Bhatnagar, S., & Mishra, V. K. (2011). An optimized SDE model for slotted aloha. IEEE Transactions on Communications, 59(6), 1502–1508.

  31. Bhatnagar, S., Prasad, H. L., & Prashanth, L. A. (2013). Stochastic recursive algorithms for optimization: Simultaneous perturbation methods., Lecture notes in control and information sciences London: Springer.

    Book  Google Scholar 

  32. Patro, R. K., & Bhatnagar, S. (2009). A probabilistic constrained nonlinear optimization framework to optimize RED parameters. Performance Evaluation, 66(2), 81–104.

    Article  Google Scholar 

  33. Karmeshu, Patel, S., & Bhatnagar, S. (2017). Adaptive mean queue size and its rate of change: Queue management with random dropping. Telecommunication Systems, 65(2), 281–295.

  34. Kushner, H. J., & Clark, D. S. (1978). Stochastic approximation methods for constrained and unconstrained systems. New York: Springer.

    Book  Google Scholar 

  35. Wang, H., & Shin, K. G. (1999). Refined design of random early detection gateways. In Proceedings of IEEE GLOBECOM (pp. 769–775).

  36. Hollot, C. V., Misra, V., Towsley, D., & Gong, W. (2002). Analysis and design of controllers for AQM routers supporting TCP flows. IEEE Transactions on Automatic Control, 47(6), 945–959.

    Article  Google Scholar 

  37. Low, S. H., Paganini, F., Wang, J., & Doyle, J. C. (2003). Linear stability of TCP/RED and a scalable control. Computer Networks Journal, 43(5), 633–647.

    Article  Google Scholar 

  38. Bhatnagar, S., & Patro, R. K. (2009). A proof of convergence of the B-RED and P-RED algorithms for random early detection. IEEE Communications Letters, 13(10), 809–811.

    Article  Google Scholar 

  39. Adams, R. (2013). Active queue management: A survey. IEEE Communations Surveys & Tutorials, 15(3), 1425–1476.

    Article  Google Scholar 

  40. Wu, Y., Min, G., & Yang, L. T. (2013). Performance analysis of hybrid wireless networks under bursty and correlated traffic. IEEE Transactions on Vehicular Technology, 62(1), 449–454.

    Article  Google Scholar 

  41. Wang, C., Li, B., Thomas Hou, Y., Sohraby, K. & Lin, Y. (2004). LRED: A robust active queue management scheme based on packet loss ratio. In Proceedings on 23rd Annual Joint Conference on IEEE INFOCOM (vol. 1, pp. 112).

  42. Bhatnagar, S., Fu, M. C., Marcus, S. I., & Wang, I. J. (2003). Two-timescale simultaneous perturbation stochastic approximation using deterministic perturbation sequences. ACM Transactions on Modelling and Computer Simulation, 13(2), 180–209.

    Article  Google Scholar 

  43. Bhatnagar, S. (2005). Adaptive multivariate three-timescale stochastic approximation algorithms for simulation based optimization. ACM Transactions on Modeling and Computer Simulation, 15(1), 74–107.

    Article  Google Scholar 

  44. Borkar, V. S. (2008). Stochastic approximation: A dynamical systems viewpoint. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  45. Bhatnagar, S., & Borkar, V. S. (1997). Multiscale stochastic approximation for parametric optimization of hidden Markov models. Probability in the Engineering and Informational Sciences, 11, 509–522.

    Article  Google Scholar 

  46. Bhatnagar, S., Fu, M. C., Marcus, S. I., & Bhatnagar, S. (2001). Two timescale algorithms for simulation optimization of hidden Markov models. IIE Transactions (Pritsker special issue on simulation), 3, 245–258.

    Google Scholar 

Download references

Author information

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
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sanjeev Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Karmeshu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shalabh Bhatnagar.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Published:

  • Issue Date:

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

Keywords