Delay-Dependent Priority-Aware Transmission Scheduling for E-Health Networks: A Mechanism Design Approach
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, the management of medical packet transmissions in electronic health (e-health) networks is studied. Unlike most existing works in the literature, we focus on beyond wireless body area network (beyond-WBAN) communications, i.e., data transmissions from WBAN-gateways (e.g., smart phones) to the base station of medical centers, and consider a delay-dependent priority-aware transmission scheduling, which jointly takes into account both the criticality of medical packets and their starving time (i.e., experienced delays). In our model, medical packets are randomly aggregated at WBAN-gateways (each of which stands for one patient), and their beyond-WBAN transmission requests are reported to the base station with different priority information, which reflects their heterogeneities in medical importance. The base station then manages the beyond-WBAN transmissions following a constructed queueing system with a delay-dependent dynamic priority discipline. With the aim of maximizing the network welfare while preventing unexpected strategic behaviors from smart gateways, we design a truthful and efficient mechanism based on a virtual delay-dependent prioritized queueing game. Analytical and simulation results examine the feasibility of the proposed mechanism and demonstrate its superiority over the counterparts.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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