Multicast routing with delay and delay variation constraints using genetic algorithm
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
The paper presents a constrained multicast routing scheme based on genetic algorithm (GA). The paper considers two constraints which represent quality of service (QoS) measures that a network should provide for real-time applications. First, a constraint on end-to-end delay from source to each destination, second, bounded delay variations along the paths from source to each destination. A genetic algorithm for delay and delay variation multicast routing (GADVM) is proposed. The performance of the proposed algorithm is evaluated through simulations and compared with four known multicast routing algorithms, namely, BSMA, CDKS, SPT, and KPP. Two performance metrics are considered, the failure rate and average cost per path. It is demonstrated that the GADVM algorithm compares favourably and gives much lower failure rates; its cost is also comparable with, and in some cases is better than, other algorithms.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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