MétaCan
Menu
Back to cohort
Record W2023858199 · doi:10.1109/icc.2013.6654769

iCAR: Intersection-based connectivity aware routing in vehicular ad hoc networks

2013· article· en· W2023858199 on OpenAlex
Nizar Alsharif, Sandra Céspedes, Xuemin Shen

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
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer networkComputer scienceNetwork packetVehicular ad hoc networkRouting protocolIntersection (aeronautics)Wireless ad hoc networkOverhead (engineering)Routing (electronic design automation)TelecommunicationsWirelessEngineeringTransport engineering

Abstract

fetched live from OpenAlex

In this paper, we propose an intersection-based connectivity-aware routing protocol (iCAR) for vehicular ad hoc networks (VANETs) to enable infotainment and interactive applications, as well as multi-hop Internet access in urban environments. iCAR is a novel protocol that takes into consideration real-time vehicular traffic information and the experienced packet delivery delay per road, in order to improve the routing performance by dynamically selecting roads with a guaranteed connectivity and a reduced delivery delay. This is achieved by deploying a microscopic view of vehicles location to proactively estimate roads connectivity and the minimum link lifetime per road. Detailed analysis and simulation-based evaluations show that iCAR significantly improves the network performance in terms of packet delivery ratio and end-to-end delay with a negligible cost of communication overhead.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.185
Teacher spread0.180 · 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

Citations77
Published2013
Admission routes1
Has abstractyes

Explore more

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