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Record W2149288627 · doi:10.1109/icton.2012.6253908

Energy-efficient DBA and QoS in FiWi networks constrained to metro-access convergence

2012· article· en· W2149288627 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer networkComputer scienceAccess networkEfficient energy useQuality of serviceWirelessNetwork packetWireless networkBandwidth (computing)Bandwidth allocationTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Fiber-Wireless (FiWi) access networks aim at combining the flexibility, ubiquity and mobility of wireless access networks with the robustness and high capacity support of the optical access networks. Several bandwidth allocation algorithms have been proposed for the convergence of fiber and wireless access networks. Besides, fiber-wireless convergence, metro-access convergence and energy-efficiency have appeared as further challenges of the ICTs. In this paper, we report our current research results on the service quality of existing energy-efficient bandwidth allocation schemes in long-reach FiWi networks, in terms of detailed delay performance, fairness and utilization. We show that deployment of energy-efficient Dynamic Bandwidth Allocation (DBA) in a FiWi network does not only guarantee energy savings throughout the day but also introduces reduced maximum packet delay for both FTTX and wireless users, enhanced delay variance for all packets and significant fairness among different parts of the network. Furthermore, energy-efficient DBA decreases average buffer occupancy at the ONUs.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.609
Threshold uncertainty score0.430

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 head0.018
GPT teacher head0.263
Teacher spread0.246 · 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

Citations9
Published2012
Admission routes1
Has abstractyes

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