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Record W2150310088 · doi:10.1002/spe.609

Performance evaluation for VBR Continuous Media File Server admission control

2004· article· en· W2150310088 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.

Bibliographic record

VenueSoftware Practice and Experience · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsUniversity of British ColumbiaUniversity of Saskatchewan
Fundersnot available
KeywordsComputer scienceControl (management)Variable bitrateOperating systemWorld Wide WebComputer networkDatabaseBit rate

Abstract

fetched live from OpenAlex

Abstract A file server for continuous media must provide resource guarantees and only admit requests that do not violate the resource availability. This paper addresses the admission performance of a server that explicitly considers the variable bit rate nature of the continuous media streams. A prototype version of the server has been implemented and evaluated in several heterogeneous environments. The two system resources for which admission control is evaluated are the disk bandwidth and the network bandwidth. Performance results from both measurement and simulation are shown with respect to different admission methods and varying scenarios of stream delivery patterns. We show that the vbrSim algorithm developed specifically for the server outperforms the other options for disk admission especially with request patterns that have staggered arrivals, while the network admission control algorithm is able to utilize a large percentage of the network bandwidth available. We also show the interactions between the limits of these two resources and how a system can be configured without wasted capacity on either one of the resources. Copyright © 2004 John Wiley & Sons, Ltd.

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)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.366
Teacher spread0.331 · 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