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Record W2111278228 · doi:10.1109/ccece.2006.277710

Integrated Routing System for Wireless Mesh Networks

2006· article· en· W2111278228 on OpenAlexaff
Muhammad Jaseemuddin, Amir Esmailpour, Ali A. Alwan, Osama Bazan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer networkWireless mesh networkComputer scienceWireless ad hoc networkOpen Shortest Path FirstBackbone networkDistributed computingMobile ad hoc networkShared meshOptimized Link State Routing ProtocolMesh networkingThroughputSwitched meshOrder One Network ProtocolRouting protocolWireless networkRouting (electronic design automation)Link-state routing protocolWirelessWireless Routing ProtocolTelecommunications

Abstract

fetched live from OpenAlex

Recently wireless mesh network (WMN) has become popular especially for its low cost deployment in the areas of poor network infrastructure and terrain of difficult deployment. Although paths in WMN backbone network are stable, the access link contention can severely constrain the end-to-end throughput. We proposed an integrated routing system for WMN that exploits both paths through the backbone network and through the ad-hoc access network of mobile nodes. The ad-hoc path is considered as an alternative path and is used only when the primary backbone path is severely constrained due to access links contention. We have shown through simulation that alternative path is effective in delivering high throughput in that situation. We also proposed a scheme for initiating the route discovery of the ad-hoc path. We investigated the use of OSPF in the backbone network and proposed solutions of dealing with multi-area OSPF configuration in the backbone and auto-configuration of OSPF wireless links

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)0.002
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 score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.006

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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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

Citations9
Published2006
Admission routes1
Has abstractyes

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