Maximizing Network Stability in a Mobile WiMax/802.16 Mesh Centralized Scheduling
Bibliographic record
Abstract
WiMax/802.16 mesh network is an emerging infrastructure that offers a cost-effective deployment for high-capacity wireless broadband access to the backhaul network. Recently, mobility in WiMax/802.16 based mesh networks has been discussed through the IEEE 802.16e standard. Hence, mesh nodes need no longer be stationary, and as a result they will be powered from energy limited batteries. In such networks, radio frequency RF-links become vulnerable to breakage due to nodes mobility and nodes are condemned to failure when their battery is depleted. Adopting this deployment strategy requires a mechanism for selecting the most stable routing paths (with the highest RF-links and nodes availability). In this paper, we develop a mathematical model that considers RF-link and node characteristics in such mesh networks and maximizes the network stability.Namely, our model takes into account the interference caused by adjacent RF-links as well as nodes mobility and energy.Results show that selecting most stable paths augments the longevity of the network's time of operation which in turn leads to a higher data delivery and more satisfied clients.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".