Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems

Buwaya, Julia; Rolim, José D. P.

doi:10.1109/dcoss.2017.39

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…In the context of the development of the VIVO platform, we launched an experiment to create a public online map of noise levels within the San Francisco Bay area using data recorded by the smartphones of private citizens 4 . The special focus of the experiment was to test load balancing and task allocation algorithms in mobile crowd-sensing applications [43], [44]. Volunteers were asked to submit non-public information about their availabilities and to download our NoiseBay app to collect anonymous noise levels.…”

Section: Noisebaymentioning

confidence: 99%

VIVO: A secure, privacy-preserving, and real-time crowd-sensing framework for the Internet of Things

Luceri

Cardoso

Papandrea

et al. 2018

Pervasive and Mobile Computing

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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 crowdsensed 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.

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Section: Noisebaymentioning

confidence: 99%