Cooperative Caching with Adaptive Prefetching in Mobile Ad Hoc Networks
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Bibliographic record
Abstract
In this paper, we propose a cooperative data caching and prefetching scheme for mobile ad hoc networks (MANETs). In this scheme, multiple hosts cooperate in prefetching and caching data. Clustering architecture was used for network organization. A weak consistency based on time to live value was used to maintain data consistency. A hybrid cache replacement policy that uses the frequency of access and reference time was employed. The effects of various parameter settings on the performance metrics such as data accessibility, query delay and network traffic overhead were investigated in a simulation environment. The proposed integrated cooperative caching and prefetching scheme was compared with cooperative caching without prefetching. The simulation results indicate that the proposed scheme improves both data accessibility and query delay at relatively lower prefetch thresholds and larger cache sizes
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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 | 0.001 |
| 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