In this paper, we present the adaptive wavelet neural network (WNN) controller, which is trained by adaptive learning rates (ALRs), as an active queue management(AQM) in end-to-end TCP network. In TCP network, AQM is important to regulate the queue length and short round trip time by passing or dropping the packets at the intermediate routers. RED and PI algorithms have been used for AQM formerly. But these algorithms show weakness in the detection and control of the congestion under dynamically changing network situations. In our method, the WNN controller using ALRs is designed to overcome the problems, which adaptively controls the dropping probability of the TCP network and is trained by gradient-descent algorithm. We apply Lyapunov theorem to verify the stability of our proposed WNN controller. The simulation results show that the performance of WNN controller using ALRs is superior to that of PI controller
[Show abstract][Hide abstract] ABSTRACT: We consider a single link accessed by a single source which responds to congestion signals from the network. The design of controllers for such sources in the presence of feedback delay has received much attention recently. Here, we present conditions for the global, asymptotic stability and semiglobal exponential stability of congestion controllers. These conditions are natural extensions of conditions obtained through linearized analysis of such systems. Our result on exponential stability provides the missing link in the proof of how one obtains a single deterministic congestion control equation from a system with many congestion-controlled sources and random disturbances. Using numerical examples, we compare the conditions on the congestion-control parameters obtained using local and global stability analysis.
IEEE Transactions on Automatic Control 07/2003; 48(6-48):1055 - 1060. DOI:10.1109/TAC.2003.812809 · 2.78 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Under the assumption that queueing delays will eventually become
small relative to propagation delays, we derive stability results for a
fluid flow model of end-to-end Internet congestion control. The
theoretical results of the paper are intended to be decentralized and
locally implemented: each end system needs knowledge only of its own
round-trip delay. Criteria for local stability and rate of convergence
are completely characterized for a single resource, single user system.
Stability criteria are also described for networks where all users share
the same round-trip delay. Numerical experiments investigate extensions
to more general networks. Through simulations, we are able to evaluate
the relative importance of queueing delays and propagation delays on
network stability. Finally, we suggest how these results may be used to
design network resources
[Show abstract][Hide abstract] ABSTRACT: Recently many active queue management (AQM) algorithms have been proposed to address performance degradations of end-to-end congestion control. However, these AQM algorithms show weaknesses to detect and control congestion under dynamically changing network situations. In this paper, we propose a predictive and robust AQM algorithm, called proportional-integral-derivative (PID)-controller, using PID feedback control the incipient as well as current congestion adaptively and proactively to dynamically changing network environments. A simulation study over a wide range of IP traffic conditions shows that PID-controller outperforms other AQM algorithms such as random early detection (RED) and proportional-integral (PI) controller in terms of the queue length dynamics, the packet loss rates, and the link utilization.
Computers and Communication, 2003. (ISCC 2003). Proceedings. Eighth IEEE International Symposium on; 01/2003
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