Mobility management in hybrid<i>ad‐hoc</i>networks and the Internet environment
Bibliographic record
Abstract
Abstract The integration of mobile ad‐hoc networks (MANETs) with the Internet provides flexible and multi‐hop communication capability in hybrid wired and wireless networks. Existing architectures for integrating these networks use Mobile IP and ad‐hoc routing protocols with fixed gateways. In this paper, we propose a mobility management scheme based on a mobile gateways (MGs) architecture. We designed a buffering mechanism for micro‐ and macro‐mobility management in hybrid networks. The performance of mobility management with optimized handover (MM‐OH), optimized handover with prediction (MM‐OHP) and forced handover (MM‐FH) are evaluated using simulation. Our simulation results show that a buffering mechanism coupled with the hybrid gateway discovery results in a higher packet delivery ratio for MM‐OH and MM‐OHP compared with the MM‐FH scheme. The MM‐OHP scheme has a lower number of handovers compared with the MM‐OH scheme. Moreover, the simulation experiments reveal that the speed of the MG has a relatively higher impact on performance than the speed of mobile nodes. Copyright © 2007 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".