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Record W2141338028 · doi:10.1109/glocom.2005.1577786

Call level service differentiation for efficient SLA management

2005· article· en· W2141338028 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

VenueGLOBECOM '05. IEEE Global Telecommunications Conference, 2005. · 2005
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsService-level agreementComputer scienceBandwidth (computing)Quality of serviceService levelComputer networkPreemptionShared resourceDifferentiated servicesService (business)Distributed computingOperating systemBusiness

Abstract

fetched live from OpenAlex

This paper presents an efficient resource sharing scheme for a network supporting multiple service level agreements (SLAs). Specifically, an overloaded SLA can borrow bandwidth from those underloaded SLAs based on a call level service differentiation concept. While flows admitted with the SLA nominal capacity are considered as in profile flows, flows admitted with borrowed bandwidth are tagged as out profile flows and may be preempted later when the original bandwidth owner needs to claim back the resources. Such preemption is considered as the quality of service (QoS) differentiation between the in profile and out profile flows. Through the implementation design and computer simulations, we show that high resource utilization and SLA compliance can be simultaneously achieved by bandwidth borrowing and call level differentiation.

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 categoriesMeta-epidemiology (narrow)
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 score0.860
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.034
GPT teacher head0.271
Teacher spread0.236 · 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