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Record W2025856120 · doi:10.1016/j.procs.2012.06.126

Multi-hop Interference-Aware Routing Protocol for Wireless Sensor Networks

2012· article· en· W2025856120 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

VenueProcedia Computer Science · 2012
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceComputer networkWireless sensor networkNetwork packetScheduling (production processes)Routing protocolDistributed computingCluster analysisSignal-to-interference-plus-noise ratioInterference (communication)Key distribution in wireless sensor networksWirelessWireless networkPower (physics)TelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

Wireless Sensor Networks (WSN) have gained much attention in recent years, however, these networks suffer from limited energy supply and noisy wireless links. Thus, efficient energy management and noise handling are key requirements in designing WSNs. This paper proposes an interference-aware and energy-aware routing algorithm such that power dissipation is uniform among all sensors. The proposed algorithm utilizes time synchronization and traffic scheduling to avoid interference. This work mathematically models the problem as node clustering optimization. Simulation results show the optimized proportions of packets sent by nodes to ensure uniform energy dissipation, as well as, reduced interference within clusters.

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)0.002
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: Methods
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0040.002
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 head0.040
GPT teacher head0.304
Teacher spread0.264 · 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