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Record W2146432102 · doi:10.1109/jsac.2005.863867

A position-based QoS routing scheme for UWB mobile ad hoc networks

2006· article· en· W2146432102 on OpenAlexaff
Atef Abdrabou, Weihua Zhuang

Bibliographic record

VenueIEEE Journal on Selected Areas in Communications · 2006
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer networkComputer scienceAdaptive quality of service multi-hop routingWireless ad hoc networkQuality of serviceMobile ad hoc networkOptimized Link State Routing ProtocolAd hoc wireless distribution serviceBandwidth (computing)Wireless Routing ProtocolDestination-Sequenced Distance Vector routingDynamic Source RoutingReservationGeographic routingDistributed computingRouting (electronic design automation)WirelessRouting protocolTelecommunications

Abstract

fetched live from OpenAlex

Ultra-wideband (UWB) wireless communication is a promising spread-spectrum technology that supports very high data rates and provides precise position information of mobile users. In this paper, we present a position-based quality-of-service (QoS) routing scheme for UWB mobile ad hoc networks. The scheme applies call admission control and temporary bandwidth reservation for discovered routes, taking into consideration the medium access control interactions. Via cross-layer design, it exploits UWB advantages at the network layer by using the position information in routing and bandwidth reservation and by supporting the multirate capability. Simulation results demonstrate that the proposed routing scheme is effective in end-to-end QoS support.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.253
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), 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

Citations66
Published2006
Admission routes1
Has abstractyes

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