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On block delivery time in Ethereum network

2022· article· en· W4315630011 on OpenAlex
Soosan Naderi Mighan, Jelena Mišić, Vojislav B. Mišić

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

VenueGLOBECOM 2022 - 2022 IEEE Global Communications Conference · 2022
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsExponential distributionBlock (permutation group theory)Node (physics)Computer scienceExponential functionDistribution (mathematics)Phase-type distributionProbability distributionGossipQueueing theoryComputer networkMathematicsStatisticsEngineeringCombinatorics

Abstract

fetched live from OpenAlex

We provide a comprehensive analytical model for block distribution in the Ethereum distribution network. We begin with a model for node connectivity based on reported measurements' and model the distribution of blocks using a Jackson network together with a priority M/G/1 queuing system. Our results show that the probability distribution of block response time is close to exponential distribution, while block delivery time exhibits a hypo-exponential distribution. Both distributions exhibit a thicker tail than the exponential distribution due to the peculiarities of the gossip-like protocol used to propagate blocks and transactions in Ethereum.

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 categoriesMeta-epidemiology (narrow), Open science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0140.010
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.268
Teacher spread0.241 · 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