Intelligent price-based congestion control for communication networks

Hao Wang, Zuohua Tian

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

19 Citations (Scopus)


Numerous active queue management (AQM) schemes have been proposed to stabilize the queue length in routers, but most of them lack adequate adaptability to TCP dynamics, due to the nonlinear and time-varying nature of communication networks. To deal with the above problems, we propose an intelligent price-based congestion control algorithm named IPC. IPC measures congestion through using an intelligent price derived from neural network. To meet the purpose of AQM, we design learning algorithms to optimize the weights of neural network and the key parameter of IPC automatically. IPC acts as an adaptive controller which is able to detect both incipient and current congestion proactively and adaptively under dynamic network conditions. The simulation results demonstrate that IPC significantly outperforms the well-known AQM algorithms in terms of stability, responsiveness and robustness over a wide range of network scenarios.

Original languageEnglish
Title of host publication2010 IEEE 18th International Workshop on Quality of Service, IWQoS 2010
PublisherIEEE, Institute of Electrical and Electronics Engineers
ISBN (Print)9781424459889
Publication statusPublished - 20 Sep 2010
Externally publishedYes
EventIEEE/ACM International Symposium on Quality of Service (IWQoS) 2010 - Beijing, China
Duration: 16 Jun 201018 Jun 2010
Conference number: 18th (Proceedings)

Publication series

NameIEEE International Workshop on Quality of Service, IWQoS
ISSN (Print)1548-615X


ConferenceIEEE/ACM International Symposium on Quality of Service (IWQoS) 2010
Abbreviated titleIWQoS 2010
Internet address


  • Active queue management
  • Congestion control
  • Neural network
  • Price
  • Proportional-integral- derivative

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