A* search based next hop selection for routing in opportunistic networks
Bibliographic record
Abstract
Opportunistic network (oppnet) is one of the challenging fields of wireless network. It is an intermittently connected mobile network where nodes are mobile and no end-to-end path exists. Connectivity among nodes is established when they are within the transmission range of each other. If a node has message to communicate and no intermediate node is available, then the message is stored in the node's buffer till an appropriate communication opportunity arises which is known as store-carry-forward paradigm. This paradigm has given Oppnets a new direction in the field of research. In any network, efficient and effective routing is very crucial. In this paper, a novel routing technique has been proposed for Oppnets named as A* based opportunistic routing (A*OR) which uses the A* searching technique to select the best forwarders towards the destination. The proposed protocol is compared with prophet, PRoWait and EDR as a benchmark protocols and is found to perform 19%, 11% and 32% better than prophet, PRoWait and EDR, respectively in terms of delivery probability.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".