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Record W4246969106 · doi:10.1109/perser.2004.1356801

Hybrid cache invalidation schemes in mobile environments

2004· article· en· W4246969106 on OpenAlexaff
Yuhang Bao, R. Alhaj, K. Barker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceCacheCache invalidationStateless protocolStateful firewallComputer networkCache algorithmsBroadcasting (networking)Smart CachePage cacheCPU cacheNetwork packet

Abstract

fetched live from OpenAlex

To make cached data consistent, the server periodically broadcasts an invalidation report to all mobile clients in its cell so that each can invalidate obsolete data items from its local cache. We present two hybrid cache invalidation schemes: Hybrid cache invalidation with simple broadcasting (HSB), and hybrid cache invalidation with attribute bit sequence broadcasting (HABSB). In these schemes the server is stateful as it stores the caching information of each mobile client in its cell to allow for long disconnections. However, the server periodically broadcasts an invalidation report similar to a stateless server. In HABSB, attribute bit sequences are added in each broadcasted invalidation report to maximize the cache-hit ratio and to reduce the data transmission of queried data items. The simulation results show that HSB and HABSB can significantly reduce the bandwidth requirement, and HABSB is very efficient in improving mobile caching.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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 designTheoretical or conceptual
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

Citations1
Published2004
Admission routes1
Has abstractyes

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