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Dynamics of random early detection

Authors: Dong Lin; Robert Morris;

Dynamics of random early detection

Abstract

In this paper we evaluate the effectiveness of Random Early Detection (RED) over traffic types categorized as non-adaptive, fragile and robust, according to their responses to congestion. We point out that RED allows unfair bandwidth sharing when a mixture of the three traffic types shares a link. This unfairness is caused by the fact that at any given time RED imposes the same loss rate on all flows, regardless of their bandwidths.We propose Fair Random Early Drop (FRED), a modified version of RED. FRED uses per-active-flow accounting to impose on each flow a loss rate that depends on the flow's buffer use.We show that FRED provides better protection than RED for adaptive (fragile and robust) flows. In addition, FRED is able to isolate non-adaptive greedy traffic more effectively. Finally, we present a "two-packet-buffer" gateway mechanism to support a large number of flows without incurring additional queueing delays inside the network. These improvements are demonstrated by simulations of TCP and UDP traffic.FRED does not make any assumptions about queueing architecture; it will work with a FIFO gateway. FRED's per-active-flow accounting uses memory in proportion to the total number of buffers used: a FRED gateway maintains state only for flows for which it has packets buffered, not for all flows that traverse the gateway.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
381
Top 10%
Top 0.1%
Top 10%
bronze