Bandwidth allocation for video delivery in wireless networks with QoE constraints for spatially random user population
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
As video streaming becomes one of the most fast growing and dominant applications in fixed and mobile networks, how to provide high quality and user satisfaction is a widely studied research topic. In this paper, we develop an analytical framework to derive the downloading rate and bandwidth requirement, so that certain objective quality of experience (QoE) constraints are met. Particularly, application-specific key performance indicators (KPIs) such as start-up delay and starvation probability are taken into account. Our analysis addresses heterogeneity of both user spatial locations and video requests. Computer simulations are conducted to verify the accuracy of the proposed analytical framework. Based on the analytical framework, a media server can adapt the downloading rate allocation, e.g., relative to the video playback rate, depending on user demands and network conditions.
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 | 0.000 |
| 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 it