Adaptive algorithms for feedback-based flow control in high-speed, wide-area ATM networks

  • Authors:
  • F. Bonomi;D. Mitra;J. B. Seery

  • Affiliations:
  • ATM Platform Organ., AT&T Network Syst., Red Bank, NJ;-;-

  • Venue:
  • IEEE Journal on Selected Areas in Communications
  • Year:
  • 2006

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Abstract

This paper gives a class of flow control algorithms for the adaptive allocation of bandwidths to virtual connections (VC) in high-speed, wide-area ATM networks. The feedback rate to the source from the network is parsimonious, with each feedback bit indicating whether the buffer at a distant switch is above or below a threshold. The service discipline at the switch is first-come-first-served. The important goal of adaptability aims to make all of the network bandwidth available to the active VCs, even though the number of such VCs is variable over a given range. Each VC has two parameters, one giving its minimum guaranteed bandwidth and the other is the weight for determining its share of the uncommitted bandwidth. Judicious selection of these parameters defines distinctive services, such as best effort and best effort with minimum bandwidth. We derive design rules for selecting the parameters of the algorithms such that the appropriate guarantees and fairness properties are exhibited in the dynamical behavior. The systematic use of “damping” in right proportion with “gain” is shown to be a powerful device for stabilizing behavior and achieving fairness. Our analyses are based on a simple analytic fluid model composed of a system of first-order delay-differential equations, which reflect the propagation delay across the network. Extensive simulations examine the following: (1) fairness, especially to start-up VCs; (2) oscillations; (3) transient behavior, such as the rate of equalization from different initial conditions; (4) disparate bandwidth allocations; (5) multiple paths with diverse propagation delays; (6) adaptability and robustness with respect to parameters; and (7) interoperability of different algorithms