Bibliographic record
Abstract
Quality of Services (QoS) routing for group communications on Internet is mainly concerned with the problem of minimization of total cost of delivery while meeting a given end-to-end delay-bound between source-receiver pairs. The core-based approach in multipoint communication enhances potential solutions in terms of QoS-efficiency and feasibility of the results in inter and intra-domain routing. In this thesis, we first analyze the solution space for constrained multipoint communication problems under the core-based approach. We show that the range of solutions examined by the models proposed to date is restricted to a subset of the entire solution space, which limits the potential efficiency of the results. We propose SPAN, a core-based framework processing on our identified extended solution space for constrained multi-source group applications. SPAN consists of core selection and tree construction as two modular components complimenting one another to achieve more efficient solutions in distributed processing. SPAN is also asymmetric, hence potentially operates in domains in which link weights are not necessarily equal in both directions. We analyze the computational and message complexity of our framework and show its feasibility for distributed deployment. Our evaluations show that SPAN consistently outperforms its counterparts in the literature. We further extended the core selection component of SPAN and present two algorithms for core selection both of which has the potential to enhance the performance of SPAN and further improve the QoS-efficiency of the solutions.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".