MétaCan
Menu
Back to cohort
Record W1995517322 · doi:10.1155/2015/539048

BandEst: Measurement-Based Available Bandwidth Estimation and Flow Admission Control Algorithm for Ad Hoc IEEE 802.15.4-Based Wireless Multimedia Networks

2015· article· en· W1995517322 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

VenueInternational Journal of Distributed Sensor Networks · 2015
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceWireless ad hoc networkComputer networkAd hoc wireless distribution serviceBandwidth (computing)Admission controlVehicular ad hoc networkOptimized Link State Routing ProtocolAlgorithmIEEE 802.11Mobile ad hoc networkWirelessWireless networkTelecommunicationsQuality of serviceNetwork packet

Abstract

fetched live from OpenAlex

We highlight different important factors that must be considered for an effective available-bandwidth-based flow admission control algorithm in ad hoc wireless networks. Moreover, we present BandEst; it is a combination of a measurement-based available bandwidth estimation technique and a flow admission control algorithm for ad hoc IEEE 802.15.4-based ad hoc networks that considers the identified factors. Extensive simulations are performed to compare BandEst with the state-of-the-art available-bandwidth-based flow admission control algorithms for ad hoc wireless networks. Our simulation results demonstrate that BandEst significantly outperforms the state-of-the-art available-bandwidth-based flow admission control algorithms for ad hoc wireless networks.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.780
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.251
Teacher spread0.228 · 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