Special Issue "Realization of Large-Scale Mobile Crowd Sensing Experiments"
Deadline for manuscript submissions: closed (31 March 2019)
Dr. Burak Kantarci
School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada
Website | E-Mail
Interests: Internet of Things; cybersecurity; big data in the network; crowdsensing and social networks; cloud networking; digital health (d-health); green ICT and sustainable communications
In recent years, the widespread availability of sensor-provided smartphones has enabled the possibility of harvesting large quantities of data in urban areas, exploiting user devices, thus, enabling so-called crowdsensing, which allows to realize complex applications that would be impossible without the involvement of the community. While many efforts have been made to improve specific techniques—spanning from signal processing to the assignment of data collection campaigns to users, and to the entire processing of data—there are still a only few attempts and experiments aimed at exploring the challenging issues raised by the management of large-scale crowdsensing campaigns as large simulations and real-world experiments.
However, as the field matures, new sensing and application opportunities emerge and Mobile Crowd Sensing (MCS) needs reproducible and repeatable test methods, as well as common and standard metrics and evaluation methodologies, that can be used to objectively quantify and compare different MCS implementations. These are critical elements to further boost the success of the MCS paradigm, which will allow practitioners and researchers to more easily build on each other's work, avoid duplication of efforts and promote cross-fertilization between complementary R&D areas.
The goal of this Special Issue is to put focus on all the above issues, by providing a consistent source of timely information and research advances in the MCS area, by identifying open research issues, discussing the limitations and/or advantages of existing solutions, and/or proposing original and innovative solutions in this challenging arena.
The main topics of this Special Issue include, but are not limited to, the following:
- Design guidelines and lessons learnt from the implementation and deployment of large-scale MCS systems;
- Scalability issues of MCS back-ends in the processing of big geolocated sensing data flows;
- Robustness, reliability, and elastic scalability of a MCS platform;
- Software tools for synthetic evaluation of large-scale MCS based on simulation and emulation approaches;
- Real-world experiences in incentivizing the recruitment of new volunteers for MCS campaigns and their long-term involvement;
- Coverage metrics measuring the quality and/or the quantity of the retrievable data in real-world as well as simulated scenarios;
- Assessment of the spatial and temporal coverage of MCS campaigns in large-scale environments, such as vast and complex urban areas;
- Assessment of citizens and community behavior in terms of social, mobility and behavioral profiles;
- Data quality in of mobile crowd-sensed data and solutions to discard inaccurate/noisy information
Dr. Luca Foschini
Dr. Michele Girolami
Dr. Burak Kantarci
Manuscript Submission Information
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