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Record W2155141687 · doi:10.1109/aina.2008.146

Using Mobile Internet Gateways in Wireless Mesh Networks

2008· article· en· W2155141687 on OpenAlexaff
Mieso K. Denko

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsComputer scienceComputer networkWireless mesh networkMultipath routingDistributed computingDynamic Source RoutingLink-state routing protocolRouting protocolPolicy-based routingWireless networkRouting (electronic design automation)WirelessTelecommunications

Abstract

fetched live from OpenAlex

Wireless mesh networks (WMNs) have recently received tremendous research attention in industry and academia. The application domain of WMN is expanding from experimental settings in academic research to practical implementations in community networking, public safety, transportation services, healthcare systems and other similar applications. While these applications are evolving, there are still key challenges in terms of network performance, flexibility and resource management. In this paper we study wireless mesh networks with mobile Internet gateways. We employ a multi-path routing scheme with a routing metric based on load balancing to reduce packet loss and delay. Unlike most existing multipath routing protocols, our approach supports the maintenance of parallel multiple paths. Simulation experiments are carried out to assess network performance in the presence of mobile gateways. Simulation results show that the use of mobile gateways with concurrent multipath routing can result in good performance at lower speed and multiple mobile gateways.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.251
Teacher spread0.222 · 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 designNot applicable
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

Citations11
Published2008
Admission routes1
Has abstractyes

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