Efficient load balancing and QoS-based location aware service discovery protocol for vehicular ad hoc networks
Bibliographic record
Abstract
Service discovery studies in vehicular networks that guarantee QoS requirements to service requesters are very important. To the best of authors' knowledge, none of the existing service discovery protocols in vehicular networks have been provided in the literature that guarantee QoS to service requesters and to the vehicular network. For efficient service discovery in vehicular networks, it is very important to provide users with services that suit better to their requests while balancing the load on service providers. Moreover, for service discovery protocol integrated with routing protocols, it is important to guarantee load balancing on routing paths between service providers and service requesters. In this article, we present a QoS aware location-based service discovery protocol for vehicular networks. Our protocol guarantees load balancing on service providers, and routing paths between service providers and service requesters. It permits also to choose service providers and routing paths between service providers and service requesters that satisfy some performance attributes specified by service requesters. We present our QoS aware protocol, prove its correctness, report on its performance evaluation, and discuss our experimental results we have obtained using realistic scenarios.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".