An Intelligent Traffic Regulator Scheme in Multimedia Networks

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 293)

Abstract

This paper proposed an intelligent and regulative traffic method for solving congestion control problems in multimedia networks. The proposed scheme, which is capable of rate-based predictive control, consists of two sub-systems: a long-term policy critic and a short-term rate-selector. Each controller in multimedia networks jointly learns the control policy by real-time interactions without prior knowledge of a network model. In addition, a reward evaluator provides reinforcement signals based on game theory to train controllers to adapt to fluctuant network environment. The well-trained controllers can take actions correctly to regulate source flow to simultaneously meet the requirements of high link utilization, low packet loss rate (PLR) and packet delay. Simulation results show that the proposed approach is effectively in controlling congestion of the multimedia traffic in internet networks.

Keywords

Congestion control Reinforcement signals 

Notes

Acknowledgments

The authors greatly appreciate to the support of the National Science Council, R.O.C., under the Grant no. NSC 101-2632-E-230-001-NY3.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer Science and Information EngineeringWuFeng UniversityChiayiTaiwan, Republic of China
  2. 2.Department of Computer Science and Information EngineeringCheng Shiu UniversityKaohsiungTaiwan, Republic of China

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