TY - GEN
T1 - Behavior-aware UAV-assisted crowd sensing technique for urban vehicular environments
AU - Barka, Ezedin
AU - Kerrache, Chaker Abdelaziz
AU - Lagraa, Nasreddine
AU - Lakas, Abderrahmane
N1 - Funding Information:
ACKNOWLEDGMENTS This research is partially supported by the United Arab Emirates University (UAEU) under grant number 31T065.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/3/16
Y1 - 2018/3/16
N2 - Measuring vehicles density and distribution in urban environments is an important task. The results of such estimation are highly required for different applications such as road lights configuration, congestion control, and also inter-vehicle data routing. This task, which is known as crowd sensing, is mostly based on smartphone-assisted sensing. However, in urban environments the multiple kinds of obstacles make it hard and mostly inaccurate especially for RoadSide Units (RSUs) low density cases. Furthermore, the assumption that all vehicles are collaborative and honest can lead to unexpected and unwanted situations. To address the above mentioned problems, we propose in this paper a trust-aware crowd sensing technique based on Unmanned Aerial Vehicle (UAV) for vehicular urban environments. Considering the real traffic information and the distribution of dishonest nodes in the network gathered by UAVs, our proposed solution provides a global view to both vehicles and RSUs, which can be used for different applications such as: finding the shortest and most trusted possible path to messages' final destinations, and also for the intelligent congestion control. Our simulation results show that our solution offers instant crowd and trust information over which in addition to the high detection ratios, also high packet delivery ratios with low network overhead are achieved.
AB - Measuring vehicles density and distribution in urban environments is an important task. The results of such estimation are highly required for different applications such as road lights configuration, congestion control, and also inter-vehicle data routing. This task, which is known as crowd sensing, is mostly based on smartphone-assisted sensing. However, in urban environments the multiple kinds of obstacles make it hard and mostly inaccurate especially for RoadSide Units (RSUs) low density cases. Furthermore, the assumption that all vehicles are collaborative and honest can lead to unexpected and unwanted situations. To address the above mentioned problems, we propose in this paper a trust-aware crowd sensing technique based on Unmanned Aerial Vehicle (UAV) for vehicular urban environments. Considering the real traffic information and the distribution of dishonest nodes in the network gathered by UAVs, our proposed solution provides a global view to both vehicles and RSUs, which can be used for different applications such as: finding the shortest and most trusted possible path to messages' final destinations, and also for the intelligent congestion control. Our simulation results show that our solution offers instant crowd and trust information over which in addition to the high detection ratios, also high packet delivery ratios with low network overhead are achieved.
KW - Crowdsensing
KW - Trust management
KW - Unmanned Aerial Vehicle
KW - Vehicular Ad-hoc Networks
UR - http://www.scopus.com/inward/record.url?scp=85046960107&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046960107&partnerID=8YFLogxK
U2 - 10.1109/CCNC.2018.8319174
DO - 10.1109/CCNC.2018.8319174
M3 - Conference contribution
AN - SCOPUS:85046960107
T3 - CCNC 2018 - 2018 15th IEEE Annual Consumer Communications and Networking Conference
SP - 1
EP - 7
BT - CCNC 2018 - 2018 15th IEEE Annual Consumer Communications and Networking Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE Annual Consumer Communications and Networking Conference, CCNC 2018
Y2 - 12 January 2018 through 15 January 2018
ER -