Analytic evaluation of RED performance
Open accessAbstract
End-to-end congestion control mechanisms such as those in TCP are not enough to prevent congestion collapse in the Internet, and they must be supplemented by control mechanisms inside the network. The IRTF has singled out random early detection (RED) as one queue management scheme recommended for rapid deployment throughout the Internet. However, RED is not a thoroughly understood scheme-witness for example how the recommended parameter setting, or even the various benefits RED is claimed to provide, have changed over the past few years. In this paper, we describe simple analytic models for RED, and use these models to quantify the benefits (or lack thereof) brought about by RED. In particular, we examine the impact of RED on the loss and delay suffered by bursty and less bursty traffic (such as TCP and UDP traffic, respectively). We find that: (i) RED does eliminate the higher loss bias against bursty traffic observed with tail drop, but not by decreasing the loss rate of bursty traffic, rather by increasing that of non bursty traffic; (ii) the number of consecutive packet drops is higher with RED than tail drop, suggesting RED might not help as anticipated with the global synchronization of TCP flows; (iii) RED can be used to control the average queueing delay in routers and hence the end to end delay, but increases the jitter of non bursty streams. Thus, applications that generate smooth traffic, such as interactive audio applications, will suffer higher loss rates and require large playout buffers, thereby negating at least in part the lower mean delay brought about by RED.
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The combination of Drop-Tail with TCP congestion avoidance may cause TCP unfairness due to a few connections that monopolize the queue space.
“(iii) TCP unfairness due to a few connections that monopolize the queue space (i.e.lock-out phenomenon).”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [68]
The combination of Drop-Tail with TCP congestion avoidance may cause unacceptable queuing delay due to a continuous full queue state.
“(ii) unacceptable queuing delay due to a continuous full queue state”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [68]
The combination of Drop-Tail with TCP congestion avoidance leads to TCP synchronization that may cause inefficient link utilization and excessive packet loss due to a simultaneous decrease in TCP rate.
“the combination of Drop-Tail with the TCP congestion avoidance mechanism leads to TCP synchronization that may cause serious problems [68,72]: (i) inefficient link utilization and excessive packet loss due to a simultaneous decrease in TCP rate”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [68]
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- Authors
- Bonald, T., May, M., & Bolot, J.-C.
- Affiliations
- Orange (France) (FR)
- École Nationale Supérieure d'Ingénieurs du Mans (FR)
- ORCID
- Bonald, T.
- Venue
- Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064)
- Publisher
- IEEE
- Published
- 2002-11-07
- Volume
- 3
- Pages
- 1415-1424
- OpenAlex
- W2127638367
- Cited by
- 405
- References
- 19
- Citations by year
- 2024: 5 · 2023: 9 · 2022: 5 · 2021: 6 · 2020: 4 · 2019: 6 · 2018: 7 · 2017: 4 · 2016: 6 · 2015: 8 · 2014: 11 · 2013: 7 · 2012: 15
- FWCI
- 26.27
- Type
- conference paper
- Language
- en
- Open access
- green
- hal.science
- Licence
- other-oa
- Locations
- IEEE Conference on Computer Communications (INFOCOM) (publishedVersion)
- HAL (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Social Sciences › Business, Management and Accounting › Management Information Systems › Advanced Queuing Theory Analysis
- Keywords
- random early detection, red, queue management, congestion control, drop tail, bursty traffic, packet loss, queuing delay, jitter, UDP, analytical model, playout buffer, Internet congestion
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