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.
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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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Hsiao, MC., Liu, CY. (2014). An Intelligent Traffic Regulator Scheme in Multimedia Networks. In: Juang, J., Chen, CY., Yang, CF. (eds) Proceedings of the 2nd International Conference on Intelligent Technologies and Engineering Systems (ICITES2013). Lecture Notes in Electrical Engineering, vol 293. Springer, Cham. https://doi.org/10.1007/978-3-319-04573-3_7
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DOI: https://doi.org/10.1007/978-3-319-04573-3_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04572-6
Online ISBN: 978-3-319-04573-3
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