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Energy Efficient Data Collection in Opportunistic Mobile Crowdsensing Architectures for Smart Cities
Capponi, Andrea; Fiandrino, Claudio; Kliazovich, Dzmitry et al.
2017In 3rd IEEE INFOCOM Workshop on Smart Cites and Urban Computing
Peer reviewed
 

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Keywords :
Mobile Crowdsensing; Smart Cities; Opportunistic Sensing
Abstract :
[en] Smart cities employ latest information and communication technologies to enhance services for citizens. Sensing is essential to monitor current status of infrastructures and the environment. In Mobile Crowdsensing (MCS), citizens participate in the sensing process contributing data with their mobile devices such as smartphones, tablets and wearables. To be effective, MCS systems require a large number of users to contribute data. While several studies focus on developing efficient incentive mechanisms to foster user participation, data collection policies still require investigation. In this paper, we propose a novel distributed and energy-efficient framework for data collection in opportunistic MCS architectures. Opportunistic sensing systems require minimal intervention from the user side as sensing decisions are application- or device-driven. The proposed framework minimizes the cost of both sensing and reporting, while maximizing the utility of data collection and, as a result, the quality of contributed information. We evaluate performance of the framework with simulations, performed in a real urban environment and with a large number of participants. The simulation results verify cost-effectiveness of the framework and assess efficiency of the data generation process.
Disciplines :
Computer science
Author, co-author :
Capponi, Andrea ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Fiandrino, Claudio ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Kliazovich, Dzmitry ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Bouvry, Pascal ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
External co-authors :
yes
Language :
English
Title :
Energy Efficient Data Collection in Opportunistic Mobile Crowdsensing Architectures for Smart Cities
Publication date :
May 2017
Event name :
3rd IEEE INFOCOM Workshop on Smart Cites and Urban Computing
Event place :
Atlanta, United States - Georgia
Event date :
May 2017
Audience :
International
Main work title :
3rd IEEE INFOCOM Workshop on Smart Cites and Urban Computing
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 12 March 2017

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