Résumé
The Internet of Things (IoT) is an emergent paradigm characterized by a plethora of smart objects connected to the Internet. An inherent characteristic of IoT is the high heterogeneity and the wide distribution of objects, thereby calling for ways to describe in an unambiguous and machine-interpretable way the resources provided by objects, their properties, and the services they offer. In this context, discovery services play a significant role as they allow clients (middleware platforms, end-users, applications) to retrieve available resources based on appropriate search criteria, such as resource type, capabilities, location, and Quality of Context (QoC) parameters. To cope with these concerns, we introduce QoDisco, a QoC-aware discovery service relying on multiple-attribute searches, range queries, and synchronous/asynchronous operations. QoDisco also comprises an ontology-based information model for semantically describing resources, services, and QoC-related information. In this paper, we describe the QoDisco architecture and information model as well as an evaluation of the search procedure in an urban air pollution monitoring scenario.
| langue originale | Anglais |
|---|---|
| titre | Ubiquitous Computing and Ambient Intelligence - 10th International Conference, UCAmI 2016, Proceedings |
| rédacteurs en chef | Carmelo R. García, Alexis Quesada-Arencibia, Mike Burmester, Pino Caballero-Gil |
| Editeur | Springer Verlag |
| Pages | 344-355 |
| Nombre de pages | 12 |
| ISBN (imprimé) | 9783319487984 |
| Les DOIs | |
| état | Publié - 1 janv. 2016 |
| Modification externe | Oui |
Série de publications
| Nom | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 10070 LNCS |
| ISSN (imprimé) | 0302-9743 |
| ISSN (Electronique) | 1611-3349 |
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