QoS-Aware Streaming in Overlay Multicast Considering the Selfishness in Construction Action
Why this work is in the frame
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Bibliographic record
Abstract
Most existing overlay multicast proposals have assumed that the nodes are cooperative and thus focus on the global topology optimization. However, a unique and important characteristic of overlay nodes is that, as application-layer agents, they can be selfish with their own interests. To achieve better quality-of-service (QoS) or to minimize forwarding overhead, an overlay node can behave selfishly in the information collection or in the overlay construction. While the former has recently been investigated, the impact of selfishness in the construction action remains unclear. In this paper, we present the first systematic study on the impact of selfishness in both tree and mesh overlay construction. Our investigation considers multiple QoS measures for streaming applications, including stream latency, resolution, and continuity. Our contribution is twofold: first, we analyze how for selfish overlay nodes to choose a construction-action policy to optimize their individual multi-metric QoS. Second, we demonstrate that the selfishness-aware policy for the construction action is consistent with the QoS optimization for the global multicast session, but not vice versa. The implication is significant: A globally optimal overlay construction itself can be vulnerable to individual selfishness; but, following our directions, we can design an overlay that is both globally optimal and selfish-resistant.
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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 | 0.000 |
| 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