MétaCan
Menu
Back to cohort
Record W2914958944 · doi:10.1109/tvt.2019.2897127

Performance Evaluation of Heterogeneous IoT Nodes With Differentiated QoS in IEEE 802.11ah RAW Mechanism

2019· article· en· W2914958944 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

VenueIEEE Transactions on Vehicular Technology · 2019
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer networkComputer scienceQuality of serviceIEEE 802.1XProtocol (science)Service setMedia access controlInter-Access Point ProtocolThroughputIEEE 802.11Wireless networkWirelessWi-FiTelecommunications

Abstract

fetched live from OpenAlex

IEEE 802.11ah protocol is specifically designed to provide network connectivity to a large number of energy efficient heterogeneous quality of service (QoS) Internet of things (IoT) devices. Restricted access window (RAW) mechanism of the protocol is an innovative feature that aims at reducing medium access contention by slotting the beacon interval and allowing limited number of nodes to contend in a specific slot. In this paper, we evaluate important medium access control (MAC) layer performance metrics of differentiated QoS IoT nodes in the IEEE 802.11ah RAW mechanism. Our analysis evaluates the feasibility of coexistence of priority and nonpriority traffic in IoT devices without degrading network performance.

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 score0.379
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.237
Teacher spread0.223 · 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