Performance evaluation of a deflection routing strategy in supra-high-speed packet switching networks
Bibliographic record
Abstract
A new analytical technique for evaluating a deflection routing strategy in a special kind of supra-high-speed (i.e., >10/sup 8/ bits/sec speed) regular digraph-type mesh networks called the Manhattan street networks (MSNs) is presented. It is based on determining the inter-node distance (IND) distribution and the topology z-transform for an ideal (i.e., the links are of infinite capacity or that the nodes are equipped with infinite buffer space) version of the network under consideration for a specific traffic distribution pattern. The value of the tuning parameter is zero for the ideal network. The tuning parameter gives the sender a flexibility which enables it to transmit packets to the intended receiver even when multiple links (or nodes) of the network are in non-operating mode. The penalty indicator depends on the network's topology and the type (i.e., directed or undirected) of communication links used in the network. The proposed analytical method is illustrated with examples, and its validity is verified by computer simulation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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 | 0.002 | 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 | 0.001 |
| 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 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".