Rate-based flow controllers for communication networks in the presence of uncertain time-varying multiple time-delays

Quet, P.-F.; Ataşlar, Banu; İftar, Altuğ; Özbay, Hitay; Kalyanaraman, Shivkumar; Kang, Taesam

doi:10.1016/s0005-1098(01)00276-x

Cited by 100 publications

(107 citation statements)

References 30 publications

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“…There is vast literature dealing with congestion control: for instance, in (Altman, Başar and Srikant, 1999), the congestion control problem is formulated as a stochastic control problem where the controls of different users are subject to different delays; in (Mascolo, 1999), the congestion control law is based on the Smith's principle; in (Quet et al, 2002), an H ∞ controller is designed guaranteeing stability robustness with respect to uncertain time-varying multiple time-delays; in (Tarbouriech et al, 2001), the congestion control problem is formulated as a robust tracking control problem, in which the target is a constant threshold on the queue length; in (Jagannathan and Talluri, 2002), a neural networkbased adaptive control methodology is developed to prevent congestion. We decided to develop a Smith predictor-based controller (see (Palmor, 1996)): in particular, we extended the algorithm in (Mascolo, 1999) to provide robust stability in the presence of time-varying delays, and we used the on-line delay estimates to render the controller adaptive; the reason of this choice is that the resulting control law is simple and easy to implement: this is a crucial requirement in the considered dynamic scenario.…”

Section: Edge Router Congestion Controlmentioning

confidence: 99%

Robust Adaptive Congestion Control for Next Generation Networks

Priscoli

Pietrabissa

2005

IFAC Proceedings Volumes

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This paper deals with the problem of congestion control in a next-generation heterogeneous network scenario. The algorithm runs in the 'edge' routers (the routers collecting the traffic between two different networks) with the aim of avoiding congestion in both the network and the edge routers. The proposed algorithm extends congestion control algorithms based on the Smith's principle: i) the controller, by exploiting on-line estimates via probe packets, adapts to the delay and rate variations; ii) the controller assures robust stability in the presence of time-varying delays.

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Section: Edge Router Congestion Controlmentioning

confidence: 99%

Robust Adaptive Congestion Control for Next Generation Networks

Priscoli

Pietrabissa

2005

IFAC Proceedings Volumes

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“…Furthermore, since the design approach in [9] is for SISO systems, the controller was designed for the multiple delays considering the longest delay and equalizing the delays in the other channels to the longest one. The case of uncertain time-varying multiple time-delays was later considered in [19], where a rate-based flow controller was designed, which is robust to variations in such delays. However, in [19], the controller was obtained by defining separate H ∞ control problems for each channel.…”

Section: Introductionmentioning

confidence: 99%

“…The case of uncertain time-varying multiple time-delays was later considered in [19], where a rate-based flow controller was designed, which is robust to variations in such delays. However, in [19], the controller was obtained by defining separate H ∞ control problems for each channel. The solutions to these problems were then weighted and blended to obtain the overall controller.…”

Section: Introductionmentioning

confidence: 99%

Robust flow control in data‐communication networks with multiple time‐delays

Ünal

Ataşlar-Ayyıldız

İftar

et al. 2010

Intl J Robust & Nonlinear

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SUMMARYRobust controller design for a flow control problem where uncertain multiple time-varying time-delays exist is considered. Although primarily data-communication networks are considered, the presented approach can also be applied to other flow control problems and can even be extended to other control problems where uncertain multiple time-varying time-delays exist. Besides robustness, tracking and fairness requirements are also considered. To solve this problem, an H ∞ optimization problem is set up and solved. Unlike previous approaches, where only a suboptimal solution could be found, the present approach allows to design an optimal controller. Simulation studies are carried out in order to illustrate the time-domain performance of the designed controllers. The obtained results are also compared to the results of a suboptimal controller obtained by an earlier approach.

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“…Then because of (16)(17)(18)(19)(20) above, S1(n+1) and S2(n+1) hold true by exactly the same steps of Case 2 in proof of Theorem 1 except that "q" gets replaced by " q ) " and the first expression " ( ) ( ) 0 q n C n > ≥ " gets replaced by " ( ) 0 q n ≥ ) ".…”

Section: Inductionmentioning

confidence: 87%

“…[6] derives stochastic optimal control policies assuming Markovmodulated capacity variations. [20] designs robust controllers to handle uncertain and heterogeneous network delays, but assumes linear operation too.…”

Section: Related Workmentioning

confidence: 99%

Time-optimal network queue control: the case of a single congested node

Iyer

Tsai

IEEE INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37

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Abstract---We solve the problem of time-optimal network queue control: what are the input data rates that make network queue sizes converge to their ideal size in the least possible time after a disturbance while still maintaining maximum link utilization at all times, even in the transient?The problem is non-trivial especially because of the vast possible heterogeneity in packet propagation delays in the network. In this paper, we derive the time-optimal queue control for a single congested network node with a single finite queue shared by flows with arbitrary network delays. We neatly separate the derivation of the optimal arrival rate sequence from that of the feedback control protocol to achieve it.The time-optimal control is robust to bandwidth and queue size estimation errors. Its complexity is only a function of the size of the network delays and no per-flow computation is needed. The time-optimality and robustness properties are proven to hold under all queue operating regimes with no need for linearizing approximations.

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Rate-based flow controllers for communication networks in the presence of uncertain time-varying multiple time-delays

Cited by 100 publications

References 30 publications

Robust Adaptive Congestion Control for Next Generation Networks

Robust Adaptive Congestion Control for Next Generation Networks

Robust flow control in data‐communication networks with multiple time‐delays

Time-optimal network queue control: the case of a single congested node

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