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Optimization flow control. I. Basic algorithm and convergence

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 t...

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Published in:IEEE/ACM transactions on networking 1999-12, Vol.7 (6), p.861-874
Main Authors: Low, S.H., Lapsley, D.E.
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Language:English
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description 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.
doi_str_mv 10.1109/90.811451
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source Association for Computing Machinery:Jisc Collections:ACM OPEN Journals 2023-2025 (reading list); IEEE Xplore (Online service)
subjects Aggregates
Algorithms
Bandwidth
Computer networks
Convergence
Costs
Delay effects
Distributed computing
Feedback
Flow control
Frequency
Links
Networks
Optimization
Projection algorithms
Utilities
title Optimization flow control. I. Basic algorithm and convergence
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