An Efficient MAC Layer Handoff Scheme for WiFi-Based Multichannel Wireless Mesh Networks
Bibliographic record
Abstract
Compared to traditional wireless networks, wireless mesh networks (WMNs) are more efficient in terms of deployment, configuration, and maintenance. However, connecting all routers through wireless connection in WMNs results in remarkably lower bandwidth of the network backbone. Multichannel technology, where non-interfering channels are used to enable mesh routers to send and receive packets simultaneously, has been extensively adopted to improve the throughput of WMNs, and providing seamless roaming in multichannel WMNs has become an important topic in WMN research. In this paper, a novel MAC layer handoff scheme is proposed as a means of minimizing handoff latency in WiFi-based multichannel WMNs for seamless communication in real-time applications. By designing a dynamic grouping algorithm for channel selection and allowing mesh routers to switch channels for probe message reply, this new scheme can shorten the waiting time for the detection of available access routers, decrease loss ratio of data packets during handoff, and consequently achieve smooth handoff in the MAC layer.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".