Protocole de découverte de services interopérable en réseau<i>ad hoc</i>
Bibliographic record
Abstract
L'expansion des reseaux sans fil temoigne de la demande croissante des utilisateurs pour un acces a des services, a tout moment. L'un des enjeux majeurs vise a decouvrir a la vo- lee les services en vue de leur utilisation. A cette fin, des protocoles de decouverte de services, toujours plus nombreux, ont ete proposes et standardises. A l'origine de nouvelles incompatibi- lites, ces protocoles demeurent inexploitables dans les reseaux ad hoc. Aussi, nous introduisons un intergiciel integrant un protocole de decouverte de services web pour reseaux ad hoc ainsi qu'un systeme de traduction de protocoles de decouverte de services afin d'offrir aux utilisa- teurs un acces transparent aux services tout en garantissant leur interoperabilite. ABSTRACT. The abundance of networked devices circumvents the need for providing access to services, anywhere, anytime. In such a context, one of the major issues lies in discovering services dynamically. For this purpose, a wide range of protocols have been proposed. While creating new sources of incompatibilities, these protocols cannot be directly deployed over MANETs, and, hence remain a major obstacle to the development of MANET-enabled services. In order to overcome these issues, we present a middleware that enables ubiquitous access to heterogeneous services based on automatic service discovery and dynamic translation of dis- covery protocols. This middleware includes a service discovery protocol customised to operate in MANETs, along with a translation component guaranteeing service interoperability.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".