MPCS: A mobility/popularity-based caching strategy for information-centric networks
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
Information-Centric Networking (ICN) has a great potential to better support the content distribution over the future Internet. Meanwhile, users with mobile devices will also access ICN, introducing a new challenge to ICN providers to handle such mobile content requests. In this paper, a mobility and popularity-based caching strategy is proposed to increase the cache hit rate through WiFi while people are moving from one WiFi hotspot to another. It thus lowers the network traffic from the local ICN to the outside Internet. Specifically, a precise derivation on the content request rate is provided based on the content popularity and user mobility. A novel caching strategy is further developed based on this derivation for both the mobility-oblivious and mobility-aware scenarios. We evaluate different caching strategies with a trace-driven simulation and our new approach can achieve a 33.84% reduction on the network traffic when compared with the caching strategies only considering the content popularity.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it