Abstract
Network congestion control algorithm decides the quality of service (QoS) of network. Based on the mechanism of TCP windows control, a fuzzy logical controller (FLC) is presented as a substitute for active queue management (AQM) algorithm to control the fluids. The FLC is applied to realize the switch between a sliding-mode controller (SMC) and a state feedback controller (SFC). Finally, the stability of the new algorithm is proved.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jacobson, V.: Congestion avoidance and control. In: Proceedings of ACM SIGCOMM 1988, Stanford, CA, pp. 314–329 (1988)
Floyd, S., Jacobson, V.: Random early detection gateways for congestion avoidance. IEEE/ACM Transactions on networking 4, 397–413 (1996)
Low, S., Paganini, F., Wang, L., et al.: Dynamics of TCP/RED and a scalable control. In: IEEE INFOCOM 2002, pp. 239–248 (2002)
Low, S., Paganini, F., Doyle, J.: Internet congestion control. IEEE control systems magazine 4, 28–43 (2002)
Floyd, S., Handley, M., Padhye, J., et al.: Equation-based congestion control for unicast applications. In: Proceedings SIGCOMM Symposium on Communications Architecture and Protocol 2000, pp. 43–56 (August 2000)
Floyd, S., Gummadi, R., Shenker, S.: Adaptive RED: An Algorithm for Increasing the Robustness of RED, Technical Report (2001)
Ott, T., Lakshman, T., Wong, L.: SRED: stabilized RED. In: Proc. of The INFOCOM 1999, New York, pp. 1346–135 (1999)
Athuraliya, S., Low, S., Li, V.: REM: active queue management. IEEE network 3, 48–53 (2001)
Low, S., Srikant, R.: A mathematical framework for designing a lowloss, low-delay Internet. Networks and Spatial Economics 4, 75–101 (2004)
Kelly, F.: Fairness and stability of end-to-end congestion control. European Journal of Control 9, 159–176 (2003)
Kelly, F.: Mathematical modeling of the Internet. Mathematics Unlimited-2001 and Beyond. Springer, Berlin (2001)
Kelly, F., Maullo, A., Tan, D.: Rate control for communication networks: shadow prices, proportional fairness, and stability. J. Oper. Res. Soc. 49(3), 237–252 (1998)
Massoulie, L.: Stability of distributed congestion control with heterogeneous feedback delays. IEEE Transactions on Automatic Control 6, 895–902 (2002)
Tian, Y.P., Yang, H.Y.: Stability of the Internet congestion control with diverse delays. Automatica 9, 1533–1541 (2004)
Srikant, R.: The mathematics of Internet congestion control. Springer, Birkhauser (2004)
Khalil, H.: Nonlinear systems, 2nd edn. Prentice Hall, Englewood Cliffs (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Song, Lh., Zhao, Ys. (2009). Dynamical Fluid Control Model on Fuzzy Control. In: Cao, By., Zhang, Cy., Li, Tf. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88914-4_50
Download citation
DOI: https://doi.org/10.1007/978-3-540-88914-4_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88913-7
Online ISBN: 978-3-540-88914-4
eBook Packages: EngineeringEngineering (R0)