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Record W2152568281 · doi:10.1109/wcnc.2011.5779285

Secure and quality of service assurance scheduling scheme for WBAN with application to eHealth

2011· article· en· W2152568281 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceComputer networkeHealthBody area networkQuality of serviceScheduling (production processes)Network packetWirelessComputer securityWireless sensor networkHealth careTelecommunications

Abstract

fetched live from OpenAlex

Wireless Body Area Network (WBAN) is gaining popularity due to its large scale of applications in eHealth. Due to its critical and real-time nature, eHealth care system must provide security, privacy, and quality of service (QoS) support, in order to provide an efficient, valuable and fully reliable assistance to patients. This paper studies packet scheduling schemes for realtime transmission in WBAN with proper security and privacy. Real-time and non real-time traffic are classified to minimize the waiting time of the eHealth application's data traffic. An efficient secure data transmission scheme in WBAN is proposed with data integrity. The scheme is user-centric and the secure key is shared among all sensors in a WBAN to minimize any additional memory and processing power requirements. Security analysis and numerical results demonstrate that our scheme can minimize the mean waiting time of a real-time traffic in WBAN and provide proper security and privacy.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.311

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 head0.027
GPT teacher head0.260
Teacher spread0.233 · 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

Citations68
Published2011
Admission routes2
Has abstractyes

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