Reference : Sociability-Driven User Recruitment in Mobile Crowdsensing Internet of Things Platforms
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/27843
Sociability-Driven User Recruitment in Mobile Crowdsensing Internet of Things Platforms
English
Fiandrino, Claudio mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Kantarci, Burak [University of Ottawa > School of Electrical Engineering and Computer Science > > ; Clarkson University > Department of Electrical and Computer Engineering]
Anjomshoa, Fazel [Clarkson University > Department of Electrical and Computer Engineering]
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) >]
Matthews, Jeanna [Clarkson University > Department of Computer Science]
Dec-2016
IEEE Global Communications Conference (GLOBECOM), Washington, DC, USA, 2016
Yes
International
IEEE Global Communications Conference (GLOBECOM), Washington, DC, USA, 2016
2016
[en] Mobile crowdsensing ; Internet of Things ; User recruitment
[en] The Internet of Things (IoT) paradigm makes the Internet more pervasive, interconnecting objects of everyday life, and is a promising solution for the development of next- generation services. Smart cities exploit the most advanced information technologies to improve and add value to existing public services. Applying the IoT paradigm to smart cities is fundamental to build sustainable Information and Communication Technology (ICT) platforms. Having citizens involved in the process through mobile crowdsensing (MCS) techniques unleashes potential benefits as MCS augments the capabilities of the platform without additional costs. Recruitment of participants is a key challenge when MCS systems assign sensing tasks to the users. Proper recruitment both minimizes the cost and maximizes the return, such as the number and the accuracy of accomplished tasks. In this paper, we propose a novel user recruitment policy for data acquisition in mobile crowdsensing systems. The policy can be employed in two modes, namely sociability-driven mode and distance-based mode. Sociability stands for the willingness of users in contributing to sensing tasks. Furthermore, we propose a novel metric to assess the efficiency of any recruitment policy in terms of the number of users contacted and the ones actually recruited. Performance evaluation, conducted in a real urban environment for a large number of participants, reveals the effectiveness of sociability-driven user recruitment as the average number of recruited users improves by at least a factor of two.
http://hdl.handle.net/10993/27843

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