Sliding mode learning based congestion control for DiffServ networks

被引：7
|
作者：
Manh Tuan Do [1 ]
Jin, Jiong [1 ]
Wang, Hai [2 ]
Man, Zhihong [1 ]
机构：
[1] Swinburne Univ Technol, Fac Engn & Ind Sci, Melbourne, Vic 3122, Australia
[2] Hefei Univ Technol, Sch Elect Engn & Automat, Hefei 3000, Peoples R China
来源：
IET CONTROL THEORY AND APPLICATIONS | 2016年 / 10卷 / 11期
关键词：
variable structure systems; DiffServ networks; robust control; learning systems; telecommunication congestion control; telecommunication traffic; delays; control engineering computing; congestion control; robust sliding mode learning control scheme; congestion control problem; differentiated service network; nonlinear network model; fluid flow theory; ordinary traffic; premium traffic; physical network resource constraints; unknown time delays; VARIABLE-STRUCTURE CONTROL; COMMUNICATION-NETWORKS; SYSTEMS; FRAMEWORK; DESIGN; TCP;
D O I：
10.1049/iet-cta.2015.0948
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this study, a robust sliding mode learning control scheme is proposed to address the congestion control problem in differentiated services (DiffServ) networks. A validated non-linear network model is based on fluid flow theory corresponding to two important services, namely, the premium traffic and the ordinary traffic. The proposed congestion controller is able to efficiently cope with both the physical network resource constraints and unknown time delays associated with networking systems. Numerical results are presented to illustrate the effectiveness of the proposed control scheme.
引用
收藏
页码：1281 / 1287
页数：7
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