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Record W2400960381 · doi:10.21307/ijssis-2017-461

A Hybrid MAC Mechanism for Multiple Load Intelligent Vehicle Transportation Network

2011· article· en· W2400960381 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 on Smart Sensing and Intelligent Systems · 2011
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTime division multiple accessComputer networkComputer scienceNetwork packetFlexibility (engineering)Mechanism (biology)Access controlChannel (broadcasting)Reliability (semiconductor)

Abstract

fetched live from OpenAlex

Abstract The Media Access Control (MAC) mechanism of intelligent vehicle communication network meets a new challenge due to the multiple load data traffic and high speed mobility. This paper proposes a hybrid MAC mechanism which takes the advantages of both TDMA and CSMA mechanism. This hybrid mechanism is based on TDMA, while CSMA mechanism is added in time slots to improve the slot utilization in both high and low load networks. Through the simulation in NS2 we compare the results of the hybrid MAC protocol with those of using CSMA and TDMA individually. It is verified that in terms of flexibility and reliability in channel utilization, packet loss ratio and fairness index, the hybrid MAC protocol is superior. The hybrid mechanism makes the MAC layer self-adaptively switch between TDMA and CSMA according to the data traffic load.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.596
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.227
Teacher spread0.201 · 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