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Record W2915576041 · doi:10.1145/3301293.3302355

Reconfigurable Streaming for the Mobile Edge

2019· article· en· W2915576041 on OpenAlexaff
Abhishek Tiwari, Brian Ramprasad, Seyed Hossein Mortazavi, Moshe Gabel, Eyal de Lara

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCloud Computing and Resource Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStream processingComputer scienceControl reconfigurationDistributed computingComputer networkEnhanced Data Rates for GSM EvolutionNetwork topologyEdge deviceTelecommunicationsEmbedded systemCloud computingOperating system

Abstract

fetched live from OpenAlex

Deploying stream computing applications on edge networks brings a new set of challenges including frequent reconfigurations due to client mobility and topology changes, geographical constraints from application semantics, state management over wide-area networks, and more. Current stream processing frameworks do not adequately address these challenges since they are designed for use inside data centers and rely on global coordination between participating nodes. Merlin is a new stream processing framework designed from the ground up for stream processing on the edge. Merlin supports fast reconfiguration without disrupting applications by decoupling data delivery from data processing and removing the need for global coordination.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score0.220

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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations19
Published2019
Admission routes1
Has abstractyes

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