Competitive analysis of buffer policies with SLA commitments
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
We consider an abstraction of the problem of managing buffers where traffic is subject to service level agreements (SLA). In our abstraction of SLAs, some packets are marked as ldquocommittedrdquo and the others are marked as ldquoexcess.rdquo The service provider must on one hand deliver all committed packets, and on the other hand can get extra revenue for any excess packet delivered. We study online algorithms managing a buffer with limited space, whose task is to decide which packets should be delivered and which should be dropped. Using competitive analysis, we show how to utilize additional buffer space and link bandwidth so that the number of excess packets delivered is comparable to the best possible by any off-line algorithm, while guaranteeing that no arriving committed packet is ever dropped. Simulations of such traffic (alone and combined with additional best-effort traffic) show that the performance of our algorithm is in fact much better than our analytical guarantees.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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