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Record W202905625

An Analytical Comparison of Distributed and Hierarchical Web-Caching Architectures.

2003· article· en· W202905625 on OpenAlexaff
Richard T. Hurley, Wenying Feng, Bingyu Li

Bibliographic record

VenueComputers and Their Applications · 2003
Typearticle
Languageen
FieldComputer Science
TopicCaching and Content Delivery
Canadian institutionsTrent University
Fundersnot available
KeywordsComputer scienceLimitingDistributed computingFalse sharingHierarchical database modelDistributed databaseServerCacheComputer networkCPU cacheCache algorithmsData mining
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we compared the mean response time of distributed and hierarchical Web-caching architectures by utilizing an analytical model. The analytical model uses simplifying assumptions for distributed and hierarchical caching systems such that they can be defined using a birth-death model. The analytical results show that the mean response time in the distributed caching system tends to be less than that of the hierarchical caching system when the arrival rate of the two caching systems is equal as well as the hit-rate of the individual caches. The analytical comparison is done for an initial condition with one client and the limiting situations where the number of clients gets large. We then use simulation to validate our conclusions in the general case.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.386

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 science0.0000.000
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 head0.269
Teacher spread0.250 · 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 designSimulation or modeling
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

Citations2
Published2003
Admission routes1
Has abstractyes

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