DTN based dominating set routing technique for mobile ad hoc networks
Bibliographic record
Abstract
With the wide spread of user mobility and the existence of various types of wireless networks, effective inter-networking is mandatory in order to support user roaming while maintaining the connectivity. In our previous work [1], we propose a system architecture to achieve the connectivity over a heterogeneous wireless network, which employs the delay-tolerant network (DTN) concept to overcome the problem of potential intermittent connections caused by user roaming and ensures quality of service (QoS) in the presence of a long disconnection period. In this paper, we present a new routing technique for mobile ad hoc networks (MANETs) based on the DTN system architecture. We introduce the concept of virtual network topology and redefine the dominating-set based routing for the challenged network environment under consideration. In addition, we propose a time based methodology to predict the probability of future contacts between node pairs to construct the virtual network topology. Simulation results demonstrate the effectiveness of the proposed dominating-set based routing scheme under the DTN system architecture.
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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) | 0.001 | 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".