| Title | Collaborative Data Delivery for Smart City-oriented Mobile Crowdsensing Systems |
|---|---|
| ID_Doc | 40573 |
| Authors | Vitello, P; Capponi, A; Fiandrino, C; Giaccone, P; Kliazovich, D; Sorger, U; Bouvry, P |
| Title | Collaborative Data Delivery for Smart City-oriented Mobile Crowdsensing Systems |
| Year | 2018 |
| Published | |
| Abstract | The huge increase of population living in cities calls for a sustainable urban development. Mobile crowdsensing (MCS) leverages participation of active citizens to improve performance of existing sensing infrastructures. In typical MCS systems, sensing tasks are allocated and reported on individual-basis. In this paper, we investigate on collaboration among users for data delivery as it brings a number of benefits for both users and sensing campaign organizers and leads to better coordination and use of resources. By taking advantage from proximity, users can employ device-to-device (D2D) communications like Wi-Fi Direct that are more energy efficient than 3G/4G technology. In such scenario, once a group is set, one of its member is elected to be the owner and perform data forwarding to the collector. The efficiency of forming groups and electing suitable owners defines the efficiency of the whole collaborative-based system. This paper proposes three policies optimized for MCS that are compliant with current Android implementation of Wi-Fi Direct. The evaluation results, obtained using CrowdSenSim simulator, demonstrate that collaborative-based approaches outperform significantly individual-based approaches. |
| https://orbilu.uni.lu/bitstream/10993/36943/1/collaborative-data-delivery.pdf |
Similar Articles
| ID | Score | Article |
|---|---|---|
67352
|
Capponi, A; Fiandrino, C; Franck, C; Sorger, U; Kliazovich, D; Bouvry, P Assessing Performance of Internet of Things-based Mobile Crowdsensing Systems for Sensing as a Service Applications in Smart Cities(2016) | |
| 45493
|
Amaxilatis, D; Lagoudianakis, E; Mylonas, G; Theodoridis, E Managing Smartphone Crowdsensing Campaigns through the Organicity Smart City Plafform(2016) | |
| 38213
|
Habibzadeh, H; Qin, Z; Soyata, T; Kantarci, B Large-Scale Distributed Dedicated- and Non-Dedicated Smart City Sensing Systems(2017)Ieee Sensors Journal, 17, 23 | |
| 41461
|
Tomasoni, M; Capponi, A; Fiandrino, C; Kliazovich, D; Granelli, F; Bouvry, P Profiling Energy Efficiency of Mobile Crowdsensing Data Collection Frameworks for Smart City Applications(2018) | |
| 41844
|
Roy, S; Ghosh, N; Ghosh, P; Das, SK bioMCS: A Bio-inspired Collaborative Data Transfer Framework over Fog Computing Platforms in Mobile Crowdsensing(2020) |