A dynamic context-aware access network selection for handover in heterogeneous network environments
Why this work is in the frame
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Bibliographic record
Abstract
Context-awareness is a key ingredient in any ubiquitous and pervasive system and provides intelligence to the system, allowing computing devices to make appropriate and timely decisions on behalf of users. One of the important aspects of mobility management is the dynamic selection of the best access network for a multimodal device when there is a need to perform a handover. Multi Attribute Decision Making (MADM) is one of the successfully used methods in the literature to solve decision making problems. The problem of access network selection has been addressed by decision making methods based on available network information. However, the quality of information is not considered. Weighted Product Method (WPM) is an MADM method that penalizes the unreliable attributes in making a decision. It does not suffer from ranking abnormalities and its cheaper computational cost makes it a suitable candidate for decision making in a dynamic situation. In this paper, an algorithm for a context-aware network selection is proposed that is based on a modified WPM for access network selection. We use a weight distribution method based on sensitivity analysis of WPM for the most influential criteria based on the state of user at a given time. Our evaluation is based on comparing WPM with TOPSIS that is successfully used in many decision making problems.
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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