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Record W2122792088 · doi:10.1109/icc.2008.919

A Novel Overlay Token Ring Protocol for Inter-Vehicle Communication

2008· article· en· W2122792088 on OpenAlexaff
J. Zhang, K.-H. Liu, Xuemin Shen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer networkComputer scienceQuality of serviceToken passingBroadcasting (networking)Token ringToken bus networkProtocol (science)StandardizationService (business)OverlaySecurity tokenWireless ad hoc networkDedicated short-range communicationsDistributed computingTelecommunicationsWireless

Abstract

fetched live from OpenAlex

Reliable and fast message dissemination for safety application and quality-of-service (QoS) guarantee for data service are considered to be the most demanding requirements in vehicle ad-hoc networks. Current medium access control (MAC) protocols are insufficient to meet both requirements, while the standardization process is still ongoing. In this paper, an overlay token ring protocol (OTRP) is proposed for inter-vehicle communication (IVC). In the OTRP, the vehicular network is considered as overlapped virtual rings, each of which has a token passed in the ring as the right for transmission. The ring structure is dynamically adjusted according to the movements of vehicles. A salient feature of the OTRP is that two operation modes, namely the normal and emergency modes, are devised, whereby timely emergency message dissemination is guaranteed and desired quality-of-service (QoS) for data service can be provided. Theoretical analysis and simulations under saturated traffic condition are conducted. The results show that the OTRP can meet the stringent requirements of vehicle communications with fast and reliable emergency message broadcasting.

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: Methods · Consensus signal: none
Teacher disagreement score0.668
Threshold uncertainty score0.514

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 head0.032
GPT teacher head0.267
Teacher spread0.235 · 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
GenreMethods

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

Citations20
Published2008
Admission routes1
Has abstractyes

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