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Cited by 1,972

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Optimization flow control. I. Basic algorithm and convergence

Low, S.H., Lapsely, D.E.·1999·IEEE/ACM Transactions on Networking
DOI 10.1109/90.811451
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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 time-varying environment. We discuss its fairness property.

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Metadata

Authors
Low, S. H., & Lapsely, D. E.
Venue
IEEE/ACM Transactions on Networking
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
1999
Volume
7
Issue
6
Pages
861-874
ISSN
1063-6692 (ISSN-L)
DOI
10.1109/90.811451
OpenAlex
W2037710455
Cited by
1,972
References
0
FWCI
64.65
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Optimization flow control. I. Basic algorithm and convergence. https://app.cochat.ai/papers/10.1109/90.811451
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Low, S. H., & Lapsely, D. E. (1999). Optimization flow control. I. Basic algorithm and convergence. IEEE/ACM Transactions on Networking. https://doi.org/10.1109/90.811451

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.