A locality preserving routing overlay using geographic coordinates
Bibliographic record
Abstract
This paper presents a design for a general locality preserving routing overlay network based on geographic coordinates of nodes. For efficient use of network resources, it is important to follow some locality principles while routing bulk multimedia content. The proposed overlay network creates the interconnection among large number of highly dynamic nodes in a completely decentralized manner, based on adaptive hierarchical partitioning of the geographical space. A major benefit of using coarse grain geographic coordinates is that they are available at off-the-shelf databases and thus do not incur additional measurement overhead. The performance of the proposed geography based routing overlay, in terms of two locality properties - stretch and route-convergence, is evaluated by simulation studies. Real topology data of 65 ISPs with presence in 534 cities across the world, collected by the RocketFuel project, is used as the basis of the simulated network. The performance results are compared with corresponding results obtained from a simulated Pastry overlay constructed on the same underlying network. The performance results show that proposed overlay has significantly better stretch and route-convergence characteristics compared to a regular Pastry network. The locality properties of the proposed routing overlay are almost equivalent to those of an optimal Pastry network where all nodes use the most proximal neighbor for each routing table row. Thus the proposed geographical routing network provides good locality properties without the overhead of proximity neighbor selection. Moreover, the proposed scheme facilitates certain geographical search applications that are difficult to realize in a Pastry overlay.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".