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Record W2073410927 · doi:10.1145/1452520.1452545

Experimental study of router buffer sizing

2008· article· en· W2073410927 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSizingRouterComputer networkComputer scienceBackbone networkNetwork packetPacket lossThroughputBuffer (optical fiber)The InternetTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

During the past four years, several papers have proposed rules for sizing buffers in Internet core routers. Appenzeller et al. suggest that a link needs a buffer of size O(C/√N), where C is the capacity of the link, and N is the number of flows sharing the link. If correct, buffers could be reduced by 99% in a typical backbone router today without loss in throughput. Enachecsu et al., and Raina et al. suggest that buffers can be reduced even further to 20-50 packets if we are willing to sacrifice a fraction of link capacities, and if there is a large ratio between the speed of core and access links. If correct, this is a five orders of magnitude reduction in buffer sizes. Each proposal is based on theoretical analysis and validated using simulations. Given the potential benefits (and the risk of getting it wrong!) it is worth asking if these results hold in real operational networks. In this paper, we report buffer-sizing experiments performed on real networks - either laboratory networks with commercial routers as well as customized switching and monitoring equipment (UW Madison, Sprint ATL, and University of Toronto), or operational backbone networks (Level 3 Communications backbone network, Internet2, and Stanford). The good news: Subject to the limited scenarios we can create, the buffer sizing results appear to hold. While we are confident that the O(C/√N) will hold quite generally for backbone routers, the 20-50 packet rule should be applied with extra caution to ensure that network components satisfy the underlying assumptions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.239
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations90
Published2008
Admission routes2
Has abstractyes

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