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Record W4403461994 · doi:10.24018/ejece.2024.8.5.650

Impact of Ad Blockers on Computer Power Consumption while Web Browsing: A Comparative Analysis

2024· article· en· W4403461994 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Electrical Engineering and Computer Science · 2024
Typearticle
Languageen
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsConsumption (sociology)Computer sciencePower consumptionWorld Wide WebPower (physics)Web navigationWeb pageArt

Abstract

fetched live from OpenAlex

This study explores the impact of various ad blockers on power consumption during web browsing, focusing on different types of online content. By analyzing power use across ten popular websites, the study assesses the performance of five widely utilized ad blockers: AdBlock, AdBlock Plus, uBlock, uBlock Origin, and uBlock Origin Lite. Power consumption was measured under controlled conditions, comparing scenarios with and without ad blockers to gain insight into their efficiency. The findings indicate substantial differences in power savings, with some ad blockers significantly reducing power usage, particularly on media-heavy sites, while others unexpectedly increased consumption under certain conditions. The study underscores the potential of ad blockers to enhance power efficiency in digital environments, highlighting the importance of optimizing ad-blocking techniques to reduce the environmental impact of online activities. Through comprehensive analysis and comparison, this research offers insights into selecting effective ad blockers to minimize power consumption, promoting more sustainable web browsing practices.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.238
Teacher spread0.226 · 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