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Record W2143512409 · doi:10.1109/icon.2000.875803

Deficits for bursty latency-critical flows: DRR++

2002· article· en· W2143512409 on OpenAlex
M.H. MacGregor, Weifeng Shi

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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceLatency (audio)TimerQueueing theoryComputer networkNetwork packetWeighted fair queueingBandwidth (computing)Real-time computingOperating systemTelecommunicationsWireless

Abstract

fetched live from OpenAlex

Fair queuing was invented to ensure that every flow gets its fair share of the total bandwidth. Efficient fair queuing using deficit round-robin, DRR, proposed by Shreedhar and Varghese (see IEEE/ACM Trans. Net., vol.4, no.4, p.386-97, 1996), reduces the work to process each packet from O(log(n)) to O(1). DRR+ was also extended to accommodate latency-critical flows. DRR+ uses a timer to police each latency-critical flow and was shown to have a latency bound of (n/sub c/s)+(M/B) for these flows. The definition of the contract of Shreedhar and Varghese, however, constrains a latency-critical flow to generate very smooth arrivals. By giving another definition of contract, we return to using the original concept of deficit to enforce each flow's commitment to its contract. This allows for bursty arrivals which may occur either as the result of source bursts, or as a result of the dynamics of multihop network paths.

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: Methods · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.424

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 head0.025
GPT teacher head0.236
Teacher spread0.212 · 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

Citations26
Published2002
Admission routes1
Has abstractyes

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