MétaCan
Menu
Back to cohort
Record W2152760865 · doi:10.1109/iwcmc.2011.5982600

Deterministic access for DSRC/802.11p vehicular safety communication

2011· article· en· W2152760865 on OpenAlexafffund
Jihene Rezgui, Soumaya Cherkaoui, Omar Chakroun

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDedicated short-range communicationsIEEE 802.11pComputer scienceComputer networkNetwork packetScheme (mathematics)WirelessVehicular ad hoc networkTransmission (telecommunications)Wireless ad hoc networkTelecommunications

Abstract

fetched live from OpenAlex

In this work, we present the design of an efficient Deterministic medium Access (DA) for Dedicated Short-Range Communication (DSRC) vehicular safety communication over IEEE 802.11p, called Vehicular DA (VDA). VDA supports two types of safety services (emergency and routine safety messages) with different priorities and strict requirements on delay, especially for emergency safety messages. VDA processes both types of safety messages to maintain a balance between two conflicting requirements: reducing chances of packets collisions and lowering the transmission delay. To avoid long delays and high packets collisions, VDA allows vehicles to access the wireless medium at selected times with a lower contention than would otherwise be possible within two-hop neighborhood by the classical 802.11p EDCA or DCF schemes. Particularly, our scheme provides an efficient adaptive adjustment of the Contention Free Period (CFP) duration to establish a priority between emergency and routine messages. Simulations show that the proposed scheme clearly outperforms the classical DCF scheme used by 802.11p in high-offered load conditions while bounding the transmission delay of safety messages.

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.

How this classification was reachedexpand

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 score0.807
Threshold uncertainty score0.711

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 science0.0010.000
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 head0.038
GPT teacher head0.246
Teacher spread0.209 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2011
Admission routes2
Has abstractyes

Explore more

Same topicVehicular Ad Hoc Networks (VANETs)French-language works237,207