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Record W2047873690 · doi:10.1504/ijahuc.2008.017004

Hybrid routing protocol with Quality of Service support for Ad Hoc Wireless Networks

2008· article· en· W2047873690 on OpenAlexaff
Amine Alaoui, Alejandro Quintero, Gabriel Ioan Ivascu

Bibliographic record

VenueInternational Journal of Ad Hoc and Ubiquitous Computing · 2008
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsComputer scienceComputer networkWireless Routing ProtocolOptimized Link State Routing ProtocolZone Routing ProtocolRouting protocolAd hoc wireless distribution serviceMobile ad hoc networkDistributed computingNode (physics)Adaptive quality of service multi-hop routingRouting (electronic design automation)Network packet

Abstract

fetched live from OpenAlex

In Mobile Ad Hoc Networks (MANETs), mobile nodes must collaborate amongst themselves to interconnect and establish communication. Moreover, their networking characteristics highlight a new breed of unresolved routing and Quality of Service problems. In this paper we present a hybrid routing protocol with quality of service support. In this protocol, each mobile node keeps in memory not only available routes to destinations but also good routes in term of quality of service. The results obtained from simulations confirm the validity of our approach and show that our protocol clearly outperforms protocols from both the proactive and reactive type.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.799
Threshold uncertainty score0.789

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 communication0.0000.001
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 head0.026
GPT teacher head0.303
Teacher spread0.277 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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