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VIVO: A secure, privacy-preserving, and real-time crowd-sensing framework for the Internet of Things.
Journal
Pervasive and Mobile Computing
ISSN
15741192
Type
journal article
Date Issued
2018-07-21
Author(s)
Luceri, Luca
Cardoso, Felipe
Papandrea, Michaela
Giordano, Silvia
Buwaya, Julia
Kundig, Stéphane
Angelopoulos, Constantinos Marios
Rolim, José
Zhao, Zhongliang
Carrera, Jose Luis
Braun, Torsten
Tossou, Aristide C.Y.
Dimitrakakis, Christos
Abstract (De)
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.
Language
English
Keywords
Mobile crowd-sensing
Internet of Things
Big data.
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Elsevier
Volume
49
Start page
126
End page
138
Pages
13
Subject(s)
Division(s)
Eprints ID
262924