Workload characterization in Web caching hierarchies
Why this work is in the frame
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Bibliographic record
Abstract
The paper uses trace-driven simulation and synthetic Web workloads to study the request arrival process at each level of a simple Web proxy caching hierarchy. The simulation results show that a Web cache reduces both the peak and the mean request arrival rate for Web traffic workloads. However, the variability of the request arrival process may either increase, decrease, or remain the same after the cache, depending on the input arrival process and the configuration of the cache. If the input request arrival process is self-similar, then the filtered request arrival process remains self-similar, though with reduced mean. Furthermore, the superposition of Web request streams from multiple child caches results in a bursty aggregate request stream. Finally, we find that a gamma distribution provides a flexible means of modeling the request arrival count distribution in hierarchical Web caching architectures.
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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