A control theoretic approach to the design of closed loop rate based flow control for high speed ATM networks

Kolarov, A.; Ramamurthy, G.

doi:10.1109/infcom.1997.635145

Cited by 52 publications

(25 citation statements)

References 4 publications

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“…In contrast to very few studies of rate-based controls in end-to-end applications, a large body of data-link algorithms exists [4], [22], [31], [39]; however, these methods often rely on routers to compute the sending rate of each flow (e.g., in ATM) and explicitly feed it back to the end flows. In the current Internet, such computation is considered too costly to be implemented in the network layer, which makes these methods unsuitable for end-to-end applications.…”

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confidence: 99%

End-to-end rate-based congestion control: Convergence properties and scalability analysis

Loguinov

Radha

2003

IEEE/ACM Trans. Networking

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Abstract-In this paper, we study several properties of binaryfeedback congestion control in rate-based applications. We first derive necessary conditions for generic binary-feedback congestion control to converge to fairness monotonically (which guarantees asymptotic stability of the fairness point) and show that AIMD is the only TCP-friendly binomial control with monotonic convergence to fairness. We then study steady-state behavior of binomial controls with n competing flows on a single bottleneck. Our main result here shows that combined probing for new bandwidth by all flows results in significant overshoot of the available bandwidth and rapid (often super-linear as a function of n) increase in packet loss. We also show that AIMD has the best scalability and lowest packet loss increase among all TCP-friendly binomial schemes. We conclude the paper by deriving the conditions necessary to achieve constant packet loss regardless of the number of competing flows n and examine one new scheme with such constant packet loss called Ideally Scalable Congestion Control (ISCC) in both simulation and streaming experiments.

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confidence: 99%

End-to-end rate-based congestion control: Convergence properties and scalability analysis

Loguinov

Radha

2003

IEEE/ACM Trans. Networking

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“…Since the congestion control concept that was introduced in [5], several attempts at control theoretic-based schemes have been made in the literature by using approaches such as optimal control [6]; linear control [7]; fuzzy and neural control [8]; predictive adaptive control [9]; and nonlinear control techniques [10], [11]. Despite these efforts, formal, quantitative, and analytical investigation of performance of large scale networks with Diff-Serv traffics have not been fully addressed and resolved.…”

Section: Introductionmentioning

confidence: 99%

A robust adaptive congestion control strategy for large scale networks with differentiated services traffic

Chen

Khorasani

2011

Automatica

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Abstract-In this paper, a robust decentralized congestion control strategy is developed for a large scale network with Differentiated Services (Diff-Serv) traffic. The network is modeled by a nonlinear fluid flow model corresponding to two classes of traffic, namely the premium traffic and the ordinary traffic. The proposed congestion controller does take into account the associated physical network resource limitations and is shown to be robust to the unknown and time-varying delays. Our proposed decentralized congestion control strategy is developed on the basis of Diff-Serv architecture by utilizing a robust adaptive technique. A Linear Matrix Inequality (LMI) condition is obtained to guarantee the ultimate boundedness of the closed-loop system. Numerical simulation implementations are presented by utilizing the QualNet and Matlab software tools to illustrate the effectiveness and capabilities of our proposed decentralized congestion control strategy.

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“…[9] derived analytically a control-theoretic fair rate allocation algorithm which allows for arbitrary control of the closed-loop performance, but its practical use is limited by high degree of implementation complexity as the round-trip delay increases. T he work by [9,10,11] proposed distributed algorithms which adapt quickly to congestion while achieving max-min fairness, either with or without minimum rate guarantee, among competing flows. The work by [12] addressed a weighted max-min fair bandwidth sharing with minimumrate guarantee, but employs per-flow state management to calculate fair rate for each flow.…”

Section: Introductionmentioning

confidence: 99%

Stabilized Edge-to-Edge Aggregate Flow Control

Ryu

Cho

Chong

2004

Lecture Notes in Computer Science

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Abstract. In this paper, we present a distributed fiow control scheme which achieves weighted max-min fair bandwidth allocation among all source-destination pairs on a per-aggregate basis within its network. The motivation behind the scheme is the absence of per-aggregate fiow control in the current Internet, resulting in inability to enforce a certain fairness on source-destination fiaws. In our scheme, the distributed algorithm to compute weighted max-min fair rates is based on PI control in feedback control theory. We mathematically prove the asymptotic stability of the algorithm in presence af aggregate fiaws with heterogeneaus round-trip delays. Through simulations we dernarrstrate the effectiveness of the proposed scheme in controlling per-aggregate fiows.

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A control theoretic approach to the design of closed loop rate based flow control for high speed ATM networks

Cited by 52 publications

References 4 publications

End-to-end rate-based congestion control: Convergence properties and scalability analysis

End-to-end rate-based congestion control: Convergence properties and scalability analysis

A robust adaptive congestion control strategy for large scale networks with differentiated services traffic

Stabilized Edge-to-Edge Aggregate Flow Control

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