Enhanced Scalable Asynchronous Cache Consistency Scheme for Mobile Environment
Bibliographic record
Abstract
An important technique to reduce the contention on the limited bandwidth of wireless channels between mobile units and base stations is caching frequently accessed data items. In the literature, two approaches were proposed for cache consistency: Stateful and Stateless. In the Stateful approach, the server has to keep information about all the mobile units in its cell. On the other hand, in the stateless approach, the server does not store any information about clients. In this paper, we propose a hybrid cache consistency approach which combines the advantages of both Stateless and Stateful approaches; our approach has several characteristics in common with the Scalable Algorithm for Cache Consistency Scheme “SACCS”, which has been reported to have advantages compared to some major previous algorithms, including TimeStamps, Signatures, Amnesic Terminals and Asynchronous Stateful. The proposed approach reduces the side-effect of the sleep-wakeup patterns, and uses new communication messages intended to invalidate only the entries changed during the sleep time. Further, we propose a better replacement policy for the mobile unit cache, which considers the size of the removed entry to improve channel utilization. Experimental results show that the proposed approach increases the mobile cache hit, reduces the delay time of queries and reduces traffic in both uplink and downlink channels.
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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 | 0.000 | 0.000 |
| 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".