Performance of symmetric and asymmetric links in wireless networks
Bibliographic record
Abstract
Wireless networks are designed to provide the enabling infrastructure for emerging technological advancements. The main characteristics of wireless networks are: Mobility, power constraints, high packet loss, and lower bandwidth. Nodes’ mobility is a crucial consideration for wireless networks, as nodes are moving all the time, and this may result in loss of connectivity in the network. The goal of this work is to explore the effect of replacing the generally held assumption of symmetric radii for wireless networks with asymmetric radii. This replacement may have a direct impact on the connectivity, throughput, and collision avoidance mechanism of mobile networks. The proposed replacement may also impact other mobile protocol’s functionality. In this work, we are mainly concerned with building and maintaining fully connected wireless network with the asymmetric assumption. For this extent, we propose to study the effect of the asymmetric links assumption on the network performance using extensive simulation experiments. Extensive simulation experiments were performed to measure the impact of these parameters. Finally, a resource allocation scheme for wireless networks is proposed for the dual rate scenario. The performance of the proposed framework is evaluated using simulation.
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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 | 0.004 | 0.020 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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".