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Record W1974608850 · doi:10.1109/mcom.2014.6807949

A survey of access management techniques in machine type communications

2014· article· en· W1974608850 on OpenAlexafffund
Mohammad Tauhidul Islam, Abd‐Elhamid M. Taha, Selim G. Akl

Bibliographic record

VenueIEEE Communications Magazine · 2014
Typearticle
Languageen
FieldEngineering
TopicIoT Networks and Protocols
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceMachine to machineAutomationControl communicationsQuality of serviceCommunications systemScheme (mathematics)TelecommunicationsComputer networkComputer securityInternet of Things

Abstract

fetched live from OpenAlex

Machine-to-machine communications can be defined as ubiquitous communications among machines to perform diversified activities such as sensing, processing, decision making, and acting on decisions. The main trait that differentiates M2M from other variations of communications is the lack of human supervision in the communications lifecycle. However, increased automation resulted in many heterogeneous novel applications taking advantage of M2M. This eventually caused an explosion in the number of devices participating in M2M. Therefore, managing the massive number of accesses to satisfy the QoS requirements of the different applications running on those devices has become an issue of great concern. In this article, we survey the existing access management approaches for M2M communication, aiming at a novel classification scheme that will serve as a guide and motivation toward further research in this area.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0020.001
Scholarly communication0.0040.005
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.073
GPT teacher head0.343
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations99
Published2014
Admission routes2
Has abstractyes

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