VIVO: A secure, privacy-preserving, and real-time crowd-sensing framework for the Internet of Things
Artikel i vetenskaplig tidskrift, 2018
Smartphones are a key enabling technology in the Internet of Things (IoT) for gathering crowd-sensed data. However, collecting crowd-sensed data for research is not simple. Issues related to device heterogeneity, security, and privacy have prevented the rise of crowd-sensing platforms for scientific data collection. For this reason, we implemented VIVO, an open framework for gathering crowd-sensed Big Data for IoT services, where security and privacy are managed within the framework. VIVO introduces the enrolled crowd-sensing model, which allows the deployment of multiple simultaneous experiments on the mobile phones of volunteers. The collected data can be accessed both at the end of the experiment, as in traditional testbeds, as well as in real-time, as required by many Big Data applications. We present here the VIVO architecture, highlighting its advantages over existing solutions, and four relevant real-world applications running on top of VIVO. (C) 2018 Elsevier B.V. All rights reserved.
Mobile crowd-sensing
Internet of Things
Big data
Författare
Luca Luceri
Universität Bern
SUPSI
Felipe Cardoso
SUPSI
Michela Papandrea
SUPSI
Silvia Giordano
SUPSI
Julia Buwaya
Universite de Geneve
Stephane Kundig
Universite de Geneve
Constantinos Marios Angelopoulos
Bournemouth University
Universite de Geneve
Jose Rolim
Universite de Geneve
Zhongliang Zhao
Universität Bern
Jose Luis Carrera
Universität Bern
Torsten Braun
Universität Bern
Aristide Tossou
Chalmers, Data- och informationsteknik, Datavetenskap
Christos Dimitrakakis
Chalmers, Data- och informationsteknik, Data Science
Aikaterini Mitrokotsa
Chalmers, Data- och informationsteknik, Nätverk och system
Pervasive and Mobile Computing
1574-1192 (ISSN)
Vol. 49 126-138Styrkeområden
Informations- och kommunikationsteknik
Ämneskategorier
Datavetenskap (datalogi)
Datorsystem
DOI
10.1016/j.pmcj.2018.07.003