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Record W2165290294 · doi:10.1109/pccc.2004.1395018

Adaptive gossip-based routing algorithm

2005· article· en· W2165290294 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE International Conference on Performance, Computing, and Communications, 2004 · 2005
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDestination-Sequenced Distance Vector routingComputer scienceAd hoc On-Demand Distance Vector RoutingDynamic Source RoutingComputer networkGossipDistance-vector routing protocolMultipath routingStatic routingOptimized Link State Routing ProtocolAlgorithmDistributed computingRouting (electronic design automation)Routing protocolPsychology

Abstract

fetched live from OpenAlex

In this paper we investigate an up-to-date gossip-based ad hoc routing algorithm (AODV+G) [Z. J. Haas, et al., 2002] implemented in ad hoc on-demand distance vector routing (AODV) and discuss its weakness with respect to overall network routing performance. An enhanced approach, adaptive gossip-based ad hoc routing (AGAR), is introduced, simulated and compared with AODV+G. We expect that AGAR would outperform more significantly in larger scaled networks.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.046
GPT teacher head0.303
Teacher spread0.257 · 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