Towards QoC-aware location-based services

International audience As location-based services on mobile devices are entering more and more everyday life, we are concerned in this paper with finding ways to master the level of quality of location information in order to take relevant decisions. Location being a typical example of context infor...

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Bibliographic Details
Main Authors: Chabridon, Sophie, Ngo, Cao Cuong, Abid, Zied, Conan, Denis, Taconet, Chantal, Ozanne, Alain
Other Authors: Algorithmes, Composants, Modèles Et Services pour l'informatique répartie (ACMES-SAMOVAR), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom Paris (IMT)-Télécom SudParis (TSP)-Institut Mines-Télécom Paris (IMT)-Télécom SudParis (TSP), Département Informatique (INF), Institut Mines-Télécom Paris (IMT)-Télécom SudParis (TSP), Centre National de la Recherche Scientifique (CNRS), Pascal Felber, Romain Rouvoy, TC 6, WG 6.1
Format: Conference Object
Language:English
Published: HAL CCSD 2011
Subjects:
Context
Quality of context
Location
Uncertainty
[INFO]Computer Science [cs]
[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing
Iceland
Online Access:https://hal.science/hal-01303054
https://hal.science/hal-01303054/document
https://hal.science/hal-01303054/file/978-3-642-21387-8_6_Chapter.pdf
https://doi.org/10.1007/978-3-642-21387-8_6
Description
Summary:International audience As location-based services on mobile devices are entering more and more everyday life, we are concerned in this paper with finding ways to master the level of quality of location information in order to take relevant decisions. Location being a typical example of context information, we manipulate it using the COSMOS framework that we develop for the management of context data and their associated quality meta-data or quality of context (QoC). We consider several QoC parameters that are important for location and determine how the QoC can help a location aggregator component to identify the current region where a user is located. The mechanisms we propose support a pragmatic approach in which application designers or deployers survey an area to demarcate regions surrounding locations, and application users are localized into these regions and are presented with the quality of the estimate. We report on the experimentation we performed on the campus of our institute collecting information from Wi-Fi, 3G networks and GPS signals, and show the accuracy we obtain at no additional infrastructure cost

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