Geographically-Distinct Request Patterns for Caching in Information-Centric Networks
Bibliographic record
Abstract
The current Internet architecture follows a hostcentric communication model, intended for machine to machine connection and message passing. Modern Internet users are mainly interested in accessing information by name, irrespective of physical location. Information centric networking (ICN) was developed to rethink Internet foundations. Innetwork caching is one of the main features of ICN. Studying the performance of different caching algorithms in ICN requires a good understanding of users' request distributions in such networks. Most studies use simplifying assumptions for user request patterns since ICNs are not yet deployed. Geographically localized and global request patterns have both been observed to possess Zipf-like properties, although the local distributions are poorly correlated with the global distribution. Several independent Zipf distributions combine to form an emergent Zipf distribution in real client request scenarios. We develop an algorithm that can generate realistic synthetic traffic for geographic regions that possesses Zipf power-law properties as well as a global Zipf distribution. Our simulation results show that the caching performance would have different behaviour based on users' requests distribution.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".