Towards end-to-end routing for periodic mobile objects
Bibliographic record
Abstract
Mobile objects can be equipped with hardware enabling them to collect data, as well as answer queries remotely and in real-time. For the latter, one needs to be able to effectively route queries from a base station to the queried object in an efficient way, i.e., with minimum energy-cost or minimum delay. A complicating factor is that in many domains the mobile objects may not form a single connected component at all times. In this paper we take advantage of periodically repeating movements to establish encounter patterns, where an encounter is defined as a time-period long enough so that sensors can communicate with each other. Possessing such encounter patterns, we show how to model the query routing problem as a shortest path problem in a graph with domain-oriented constraints, and we also present polynomial time algorithms to find the guaranteed minimal delay and minimal energy routes. Furthermore, our experiments show that the minimal energy routes found by our algorithm have a cost of less than 1% of the cost obtained when using a flooding-based protocol.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".