Assessing the Expected Performance of the OLSR Routing Protocol for Denser Urban Core Ad Hoc Network Deployments
Bibliographic record
Abstract
The wide-scale adoption of smart phones has begun to provide a pragmatic real-world deployment environments for mobile ad hoc networks, (i.e., as peer-to-peer game platforms, for emergency services, etc.). Such deployments are likely to occur with urban cores where device densities would easily exceed those that have traditionally been studied. Moreover, the quality of the resulting solutions will innately rest on the capabilities of the underlying routing protocols. Of current protocols, the OLSR proactive routing protocol makes the strongest arguments regarding its suitability to such larger, denser network environments. This work tests OLSR's true suitability by analyzing its performance within a 360-node network existing within a standard 1 km ×1.5 km communications area, (i.e., innately for a network with approximately 3 × the node densities typically studied). It is shown that OLSR largely fails for such denser networks, with these failure arising due to OLSR's underlying presumption that routing tables updates should occur relatively infrequently. This limitation within OLSR has not been previously reported and this work highlights the reasons why these issues were likely not observed within prior OLSR studies.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".