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Record W2092186628 · doi:10.1002/wcm.1064

A MAC protocol for cognitive wireless sensor body area networking

2010· article· en· W2092186628 on OpenAlexaff
Khaled A. Ali, Jahangir H. Sarker, Hussein T. Mouftah

Bibliographic record

VenueWireless Communications and Mobile Computing · 2010
Typearticle
Languageen
FieldComputer Science
TopicCognitive Radio Networks and Spectrum Sensing
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceComputer networkProtocol (science)Wireless sensor networkWirelessReverse Address Resolution ProtocolTelecommunicationsWorld Wide WebInternet ProtocolThe InternetMedicine

Abstract

fetched live from OpenAlex

Abstract In this paper, a Cognitive Radio Based Medium Access Control (CR‐MAC) protocol for Wireless Sensor Body Area Networks (WSBAN) that utilizes cognitive radio transmission is proposed. In this proposal, the sensor nodes are classified into nodes of life‐critical health information and nodes of non‐critical health information. The CR‐MAC protocol prioritizes the critical packets access to the transmission medium by transmitting them with higher power while transmitting lower priority packets using lower transmission power. At the receiver, a higher priority packet experiences collision only when there are more than one critical packet transmission at the same transmission slot while non critical packets experience collision when there are more than one transmission at the same transmission slot. This protocol is evaluated analytically and through simulation. The obtained results demonstrate a differentiated service system which prioritizes critical traffic access to the transmission medium and increases the critical traffic throughput. Copyright © 2010 John Wiley & Sons, Ltd.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.030
GPT teacher head0.314
Teacher spread0.284 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations6
Published2010
Admission routes1
Has abstractyes

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