A Centrality-Based History Prediction Routing Protocol for Opportunistic Networks
Bibliographic record
Abstract
In Opportunistic networks (OppNets), due to high mobility, short radio range, intermittent links, unstable topology, sparse connectivity, to name a few, routing is a very challenging task since it relies on cooperation between the nodes. This paper focuses on using the concept of centrality to alleviate this task. Unlike other nodes in the network, central nodes are those that are more likely to act as communication hubs to facilitate the message forwarding and thereby routing. In this paper, a recently proposed History-Based Prediction Routing protocol (HBPR) for OppNets is re-designed using this concept, yielding the so-called centrality-based HBPR (CHBPR) routing protocol. The proposed CHBPR scheme is evaluated by simulations using the Opportunistic NEtwork (ONE) simulator, showing superior performance compared to HBPR without centrality and Epidemic protocol with centrality, in terms of number of messages delivered at destination and overhead ratio, under varying number of nodes and Time-to-Live.
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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 | 0.000 |
| Open science | 0.001 | 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".