Reference : Assessing Performance of Internet of Things-based Mobile Crowdsensing Systems for Sen...
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/28784
Assessing Performance of Internet of Things-based Mobile Crowdsensing Systems for Sensing as a Service Applications in Smart Cities
English
Capponi, Andrea mailto [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) > >]
Franck, Christian [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Sorger, Ulrich [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
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) >]
Dec-2016
8th IEEE International Conference on Cloud Computing Technology and Science (CloudCom)
Yes
International
8th IEEE International Conference on Cloud Computing Technology and Science (CloudCom)
Dec 2016
Luxembourg
Luxembourg
[en] Mobile Crowdsensing ; IoT ; Smart Cities
[en] The Internet of Things (IoT) paradigm makes the Internet more pervasive. IoT devices are objects equipped with computing, storage and sensing capabilities and they are interconnected with communication technologies. Smart cities exploit the most advanced information technologies to improve public services. For being effective, smart cities require a massive amount of data, typically gathered from sensors. The application of the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms and to produce a large amount of data following Sensing as a Service (S^2aaS) business models. Having citizens involved in the process through mobile crowdsensing (MCS) techniques unleashes potential benefits as MCS augments the capabilities of existing sensing platforms. To this date, it remains an open challenge to quantify the costs the users sustain to contribute data with IoT devices such as the energy from the batteries and the amount of data generated at city-level. In this paper, we analyze existing solutions, we provide guidelines to design a large-scale urban level simulator and we present preliminary results from a prototype.
http://hdl.handle.net/10993/28784

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