Modeling and Evaluation of a Metadata-Based Adaptive P2P Video-Streaming System
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
In this paper, we present a multi-parent adaptive video-streaming system (MAVSS). MAVSS is a cooperative video-streaming system, based on the peer-to-peer (P2P) content distribution concept, to simultaneously adapt and stream video contents to heterogeneous users. In order to ensure video codec independence, we emphasize on structured, metadata-based adaptation. Therefore, MPEG-21 generic Bitstream syntax description is chosen to describe the parts of the video contents selected for adaptation operations. Additionally, without an optimal solution, it is hard to judge the efficiency of such systems. Therefore, in this paper, we first present the fundamental properties of MAVSS. We then present a mathematical model of the adaptive streaming system, where we define efficient streaming as an optimization of a cost function that can be solved as an integer linear programming problem. The model illustrates the relation among all the parameters that affect the resource contribution, resource utilization, load balancing and service fairness. We use this model to analyze the trade-offs that exist between service fairness and system efficiency.
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 | 0.004 | 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 | 0.001 |
| 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