MétaCan
Menu
Back to cohort
Record W2053990076 · doi:10.1145/1352533.1352552

Minimum node degree and κ-connectivity for key predistribution schemes and distributed sensor networks

2008· article· en· W2053990076 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSecurity in Wireless Sensor Networks
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWireless sensor networkComputer scienceNode (physics)Key (lock)Degree (music)Random graphTheoretical computer scienceGraphDistributed computingTopology (electrical circuits)Computer networkMathematicsComputer securityEngineeringPhysicsCombinatorics

Abstract

fetched live from OpenAlex

Connectivity is a desired property for distributed sensor networks (DSNs)secured by key predistribution schemes (KPSs). Previous research has studied whether a DSN is connected using the random graph model, but there has been no research on how strong the connectivity is. In this paper, we give results on the minimum node degree and κ-connectivity for DSNs secured by random KPSs and deterministic KPSs. As well, we use computer simulations to verify our results and validate the use of the random graph model in computing the connectivity of DSNs.

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 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 score0.933
Threshold uncertainty score0.886

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.235
Teacher spread0.206 · 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

Quick stats

Citations5
Published2008
Admission routes1
Has abstractyes

Explore more

Same topicSecurity in Wireless Sensor NetworksFrench-language works237,207