Rate control algorithms for the ATM ABR service

Hernandez-Valencia, E.; Benmohamed, Lotfi; Nagarajan, R.; Chong, Song

doi:10.1002/ett.4460080104

Cited by 27 publications

(14 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We have not discussed convergence to equilibrium and an interesting and challenging question concerns whether rate control algorithms such as those described in [2], [3], and [4] may be adapted to implement the proportional fairness criterion described in this paper.…”

Section: Discussionmentioning

confidence: 99%

Charging and rate control for elastic traffic

Kelly

1997

Trans Emerging Tel Tech

2,498

1,847

View full text Add to dashboard Cite

This paper addresses the issues of charging, rate control and routing for a communication network carrying elastic traffic, such as an ATM network offering an available bit rate service. A model is described from which max-min fairness of rates emerges as a limiting special case; more generally, the charges users are prepared to pay influence their allocated rates. In the preferred version of the model, a user chooses the charge per unit time that the user will pay; thereafter the user's rate is determined by the network according to a proportional fairness criterion applied to the rate per unit charge. A system optimum is achieved when users' choices of charges and the network's choice of allocated rates are in equilibrium.

show abstract

Section: Discussionmentioning

confidence: 99%

Charging and rate control for elastic traffic

Kelly

1997

Trans Emerging Tel Tech

2,498

1,847

View full text Add to dashboard Cite

show abstract

“…At times link prices are unchanged, i.e., Similarly, let be a set of times at which source updates its rate. At times At times link computes an estimate of the gradient and updates its price according to (14) The estimate is computed using aggregate past source rates at link [cf. (8) (19) where is given by (6), and…”

Section: Asynchronous Distributed Algorithmmentioning

confidence: 99%

“…As in [32], the key to the proof is to show that the price adjustment (14) remains in the descent direction and hence, the value of the dual-objective function is decreased in each iteration. The proof in our case is somewhat more complicated because, since our minimization is a dual problem, the gradient estimate depends on previous prices in a more complex way through (15)-(33).…”

Section: Asynchronous Distributed Algorithmmentioning

confidence: 99%

Optimization flow control. I. Basic algorithm and convergence

Low

Lapsley

1999

IEEE/ACM Trans. Networking

1,728

1,505

View full text Add to dashboard Cite

Abstract-We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using a gradient projection algorithm. In this system, sources select transmission rates that maximize their own benefits, utility minus bandwidth cost, and network links adjust bandwidth prices to coordinate the sources' decisions. We allow feedback delays to be different, substantial, and time varying, and links and sources to update at different times and with different frequencies. We provide asynchronous distributed algorithms and prove their convergence in a static environment. We present measurements obtained from a preliminary prototype to illustrate the convergence of the algorithm in a slowly timevarying environment. We discuss its fairness property.

show abstract

“…In the ATM ABR context the primary concern has been to develop algorithms which adapt quickly to congestion while trying to be fair in a so-called sense [5], [13], [16]. This notion of fairness is different from the notion of the solutions in game theory.…”

mentioning

confidence: 99%

A game theoretic framework for bandwidth allocation and pricing in broadband networks

Yaïche

Mazumdar

Rosenberg

2000

IEEE/ACM Trans. Networking

617

435

View full text Add to dashboard Cite

Abstract-In this paper, we present a game theoretic framework for bandwidth allocation for elastic services in high-speed networks. The framework is based on the idea of the Nash bargaining solution from cooperative game theory, which not only provides the rate settings of users that are Pareto optimal from the point of view of the whole system, but are also consistent with the fairness axioms of game theory. We first consider the centralized problem and then show that this procedure can be decentralized so that greedy optimization by users yields the system optimal bandwidth allocations. We propose a distributed algorithm for implementing the optimal and fair bandwidth allocation and provide conditions for its convergence. The paper concludes with the pricing of elastic connections based on users' bandwidth requirements and users' budget. We show that the above bargaining framework can be used to characterize a rate allocation and a pricing policy which takes into account users' budget in a fair way and such that the total network revenue is maximized.

show abstract

Rate control algorithms for the ATM ABR service

Cited by 27 publications

References 31 publications

Charging and rate control for elastic traffic

Charging and rate control for elastic traffic

Optimization flow control. I. Basic algorithm and convergence

A game theoretic framework for bandwidth allocation and pricing in broadband networks

Contact Info

Product

Resources

About