Analyzing Document-Duplication Effects on Policies for Browser and Proxy Caching
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
Browser and proxy-server caching are effective and relatively inexpensive methods of improving Web performance. Most existing research considers caching to occur independently at the browser and the proxy server. When the browser and the proxy-server cache independently, documents may get duplicated across the two levels. This paper analyzes the impact of document duplication on the performance of several browser-proxy caching policies. We first derive an exact expression and an accurate approximation for the delay under a joint browser-proxy caching policy in which no duplication is permitted. This policy is compared to a base or benchmark policy in which caching occurs independently at the two levels, and hence, duplication of documents is freely permitted. We next propose a more general caching policy in which a controlled amount of duplication is permitted. This policy is analyzed and an exact expression and an approximate expression for performance are derived. Finally, a simulation study is performed to confirm the accuracy of the theoretical results and extend these results for situations that are difficult to analyze mathematically.
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 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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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