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

Content Provider	ACM Digital Library
Author	Loguinov, Dmitri Radha, Hayder
Abstract	In this paper, we study several properties of binary-feedback 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 $\textit{only}$ TCP-friendly binomial control with monotonic convergence to fairness. We then study steady-state behavior of binomial controls with $\textit{n}$ 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 $\textit{n})$ 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 $\textit{n}$ and examine one new scheme with such constant packet loss called ideally scalable congestion control in both simulation and streaming experiments.
Starting Page	564
Ending Page	577
Page Count	14
File Format	PDF
ISSN	10636692
DOI	10.1109/TNET.2003.815291
Volume Number	11
Issue Number	4
Journal	IEEE/ACM Transactions on Networking (TON)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2003-08-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	MPEG-4 Binomial algorithms Congestion control Multimedia streaming Packet loss scalability
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Networks and Communications Software Computer Science Applications

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