Reference : Energy-Efficient Data Acquisition in Mobile Crowdsensing Systems
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Energy-Efficient Data Acquisition in Mobile Crowdsensing Systems
Capponi, Andrea mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
19th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Chania, Greece, 2018
19th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WOWMOM)
June 2018
[en] Mobile crowdsensing ; Energy efficiency ; Data collection
[en] Mobile Crowdsensing (MCS) is one of the most promising paradigms for monitoring phenomena in urban environments. The success of a MCS campaign relies on large participation of citizens, who may be reluctant in joining a campaign due to sensing and reporting costs they sustain. Hence, it is fundamental to propose efficient data collection frameworks (DCFs). In the first stages of our work, we proposed an energyefficient DCF that aims to minimize energy consumption while maximizing the utility of contributed data. Then, we developed an Android application and proposed a methodology to compare several DCFs, performing energy- and network-related measures with Power Monitor and Wireshark. Currently, we are investigating collaborative data delivery as a more efficient solution than the individual one. The key idea is to form groups of users and elect a responsible for aggregated data delivery. To this end, it is crucial to analyze device to device (D2D) communications and propose efficient policies for group formation and owner election. To evaluate the performance in realistic urban environments we exploit CrowdSenSim, which runs large-scale simulations in citywide scenarios.

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