Scalable and fault-tolerant support for variable bit-rate data in the exedra streaming server
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 describe the design and implementation of the Exedra continuous media server, and experimentally evaluate alternative resource management policies using a prototype system that we built. Exedra has been designed to provide scalable and efficient support for variable bit-rate media streams whose compression efficiency leads to reduced storage space and bandwidth requirements in comparison to constant bit-rate streams of equivalent quality. We examine alternative disk striping policies, and quantify the benefits of innovative techniques for storage space allocation, buffer management, and resource reservation, which we developed to achieve both predictability and high-performance in handling disk and network data transfers of variable size. Additionally, we investigate the differences between diverse data replication schemes over disk arrays, and compare methods for disk access time reservation that enable tolerance of disk failures at minimal cost. Overall, we demonstrate the feasibility of building network media servers that exploit the latest advances in media compression technology towards reducing the cost of wide-scale streaming services for stored data.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 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