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Record W2156715704 · doi:10.1109/sensorcomm.2007.21

An Adaptive MAC Protocol for Infrastructure Wireless Sensor Networks

2007· article· en· W2156715704 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

VenueInternational Conference on Sensor Technologies and Applications · 2007
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer networkComputer scienceTime division multiple accessScalabilityWireless sensor networkNetwork topologyOverhead (engineering)Base stationProtocol (science)Efficient energy useDistributed computingEngineering

Abstract

fetched live from OpenAlex

This paper proposes ISS-Mac, an efficient MAC protocol for infrastructure-supported low-power wireless sensor networks. A central base station (sink node) is responsible for wide-network synchronization and multi-hop TDMA slots allocation. Providing an accurate topology information to the base station requires a lot of signaling overhead which affects energy efficiency of the protocol. We propose a progressive topology construction scheme to minimize this overhead and enhance scalability. In addition, the protocol facilitates integration of new nodes into the network while operation. Performance evaluation of the protocol shows that it achieves high energy savings compared to the popular S-MAC and the Full Active CSMA protocols.

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: Methods · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score0.918

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 science0.0010.000
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 head0.029
GPT teacher head0.318
Teacher spread0.289 · 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