Performance comparison of alternative Web caching techniques
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.
Bibliographic record
Abstract
Web caching is a popular technique to improve the performance and scalability of the Web by increasing document availability and enabling download sharing. Distributed cache cooperation, a mechanism for sharing documents between caches, can further improve performance by providing a shared cache to a large user population. Layer 5 switching-based transparent Web caching schemes intercept HTTP requests and redirect requests according to their contents. This technique not only makes the deployment and configuration of the caching system easier, but also improves its performance by redirecting non-cacheable HTTP requests to bypass cache servers. In this paper, we compare the performance of a number of cooperative (ICP and Cache Digest) and transparent (L5 transparent Web caching and LB-L5) Web caching techniques. We conduct a number of simulation experiments under different HTTP request intensities, network link delays and populations of cooperating cache servers. The relative merits of the different schemes are reported.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it