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Record W4249822786 · doi:10.1145/500213.500232

Preemptive bandwidth allocation protocol for multicast, multi-streams environments

2001· article· en· W4249822786 on OpenAlex
Nawel Chefaï, Nicolas D. Georganas, Gregor von Bochmann

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

VenueProceedings of the ninth ACM international conference on Multimedia - MULTIMEDIA '01 · 2001
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceMulticastComputer networkDistributed computingBandwidth (computing)Quality of serviceBandwidth allocationDynamic bandwidth allocation

Abstract

fetched live from OpenAlex

In this paper, we present a protocol that allocates resources in communication networks in order to assure specific QoS characteristics as requested by new connections. The design takes into consideration the possibility for the network allocation to adapt to application requirements.The proposed protocol uses a Bandwidth Preemptive Algorithm that permits adaptive bandwidth allocation in multicast, multi-stream environments. This design has been inspired by the one proposed by Sakate [1] where a centralized methodology is used. In our approach, we use a distributed methodology where we change the behavior of the communication service and allow the continuation of the service under more severe conditions. In other words, when there is a lack of bandwidth for a new connection, the communication service will try to find the missing bandwidth within the existent connections (or streams) when looking for a feasible path on a hop-by-hop basis, starting from the destination to an a on-tree node.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0040.001
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 head0.061
GPT teacher head0.321
Teacher spread0.259 · 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