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Record W2613908248 · doi:10.23977/cpcs.2016.11005

Design and Implementation of a High Performance Event-Driven WebSocket

2016· article· en· W2613908248 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueComputing Performance and Communication systems · 2016
Typearticle
Languageen
FieldEngineering
TopicEmbedded Systems and FPGA Design
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsComputer scienceServerEvent (particle physics)Computer networkNode (physics)The InternetOperating systemWorld Wide Web

Abstract

fetched live from OpenAlex

In recent years, instant messaging has been more and more widely used on the Internet. The Pull model adopted in the traditional servers can not well meet the requirements of real-time information acquisition and high concurrent using accesses in the practical applications. In order to deal with the aforementioned problem, using the Push model in the real-time message transmission has become a research hotspot. Firstly, based on the open source projects of Node.js, Redis and RabbitMQ, a WebSocket server which can provide real-time message push service to a large number of different users' subscription requests is designed and implemented. Secondly, the function modules and implementation details of each layer are analyzed in detail. At last, experimental results show that the feasibility of WebSocket server.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.386

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 studies0.0000.000
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 head0.019
GPT teacher head0.249
Teacher spread0.230 · 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