A cloud-based parallel system for locating customers in indoor malls

Álvarez, P. (Universidad de Zaragoza) ; Hernández, N. ; Fabra, J. (Universidad de Zaragoza) ; Ocaña, M.

Resumen: Advances in techniques of locating mobile users have promoted the development of marketing campaigns based on customers’ location. WiFi-based location methods have proven their usefulness in tracking and locating customers within a indoor mall. Nevertheless, in some cases the performance of these methods prevents them from being used in real scenarios. In this paper, we have faced the problem of improving the execution time and reducing the cost of one of these WiFi-based location methods. Parallel programming techniques, service-oriented technologies and the cloud computing paradigm have been combined to solve efficiently these problems. The resulting system has been deployed in the Amazon EC2 environment, evaluating different configuration and deployment options.

Idioma: Inglés

Año: 2019

Publicado en: CEUR Workshop Proceedings 2498 (2019), 109-116
ISSN: 1613-0073

Originalmente disponible en: Texto completo de la revista

Factor impacto SCIMAGO: 0.177 - Computer Science (miscellaneous)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2017-84796-C2-2-R
Financiación: info:eu-repo/grantAgreement/ES/UZ/JIUZ-2018-TEC-04

Tipo y forma: Article (Published version)

Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)