A Study on Vertical Handoff for Integrated WLAN and WWAN with Micro-Mobility Prediction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The integration of the third generation (3G) wireless wide-area networks (WWAN) and the IEEE 802.11 wireless local-area networks (WLAN) has drawn much attention from both industry and academia. To achieve an effective and efficient integration between the two networks with very different characteristics, nonetheless, is still an open issue. One of the challenges is to provide an integrated strategy for achieving a seamless vertical handoff of mobile users roaming between the two network domains where the delay, delay jitter, and packet loss probability can be well controlled. This paper is committed to study a two-step vertical handoff mechanism based on linear regression which is further modeled through an analytical approach. The proposed vertical handoff scheme is characterized by its adaptability to different quality of service (QoS) requirements by manipulating a threshold on the expected handoff instant. A new approach of mobility analysis is introduced to facilitate modeling of vertical handoff delay by taking advantage of Markov chain techniques. We have seen merits gained in our scheme in achieving a good trade-off between the average handoff delay and the multi-tunnel time by manipulating a threshold value, where both analytical and simulation results prove the effectiveness.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it