Abstract
Drone swarming involves multiple unmanned aerial vehicles (UAVs), which are able to manoeu-ver autonomously, providing a vast range of surveillance applications such as traffic evaluations, driver monitoring, disaster management, temporary network support, and pedestrian tracking. All these applications are an integral part of urban surveillance. In other words, cooperation between multiple drones can facilitate urban surveillance while being able to provide high-quality 3D visualization of the surroundings. This 3D representation is driven by the initiation of accurate and non-overlapping waypoints. Such efficient localization depends on the type of context and its security validation by the receiving entities. For example, a highly burdened context with negligible security is of limited use. This article presents a novel solution that is capable of securing the context information for sharing 3D waypoints between UAVs. The proposed approach achieves optimal localization through hierarchical context-aware aspect-oriented Petri nets while being powered by a novel drone context-exchange protocol for security validations.
| Original language | English |
|---|---|
| Pages (from-to) | 120-128 |
| Number of pages | 9 |
| Journal | IEEE Communications Magazine |
| Volume | 56 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Apr 2018 |
Fingerprint
ASJC Scopus subject areas
- Computer Science Applications
- Computer Networks and Communications
- Electrical and Electronic Engineering
Cite this
Secure and efficient context-aware localization of drones in urban scenarios. / Sharma, Vishal; Jayakody, Dushantha Nalin K.; You, Ilsun; Kumar, Ravinder; Li, Jun.
In: IEEE Communications Magazine, Vol. 56, No. 4, 04.2018, p. 120-128.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Secure and efficient context-aware localization of drones in urban scenarios
AU - Sharma, Vishal
AU - Jayakody, Dushantha Nalin K.
AU - You, Ilsun
AU - Kumar, Ravinder
AU - Li, Jun
PY - 2018/4
Y1 - 2018/4
N2 - Drone swarming involves multiple unmanned aerial vehicles (UAVs), which are able to manoeu-ver autonomously, providing a vast range of surveillance applications such as traffic evaluations, driver monitoring, disaster management, temporary network support, and pedestrian tracking. All these applications are an integral part of urban surveillance. In other words, cooperation between multiple drones can facilitate urban surveillance while being able to provide high-quality 3D visualization of the surroundings. This 3D representation is driven by the initiation of accurate and non-overlapping waypoints. Such efficient localization depends on the type of context and its security validation by the receiving entities. For example, a highly burdened context with negligible security is of limited use. This article presents a novel solution that is capable of securing the context information for sharing 3D waypoints between UAVs. The proposed approach achieves optimal localization through hierarchical context-aware aspect-oriented Petri nets while being powered by a novel drone context-exchange protocol for security validations.
AB - Drone swarming involves multiple unmanned aerial vehicles (UAVs), which are able to manoeu-ver autonomously, providing a vast range of surveillance applications such as traffic evaluations, driver monitoring, disaster management, temporary network support, and pedestrian tracking. All these applications are an integral part of urban surveillance. In other words, cooperation between multiple drones can facilitate urban surveillance while being able to provide high-quality 3D visualization of the surroundings. This 3D representation is driven by the initiation of accurate and non-overlapping waypoints. Such efficient localization depends on the type of context and its security validation by the receiving entities. For example, a highly burdened context with negligible security is of limited use. This article presents a novel solution that is capable of securing the context information for sharing 3D waypoints between UAVs. The proposed approach achieves optimal localization through hierarchical context-aware aspect-oriented Petri nets while being powered by a novel drone context-exchange protocol for security validations.
UR - http://www.scopus.com/inward/record.url?scp=85045755005&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85045755005&partnerID=8YFLogxK
U2 - 10.1109/MCOM.2018.1700434
DO - 10.1109/MCOM.2018.1700434
M3 - Article
AN - SCOPUS:85045755005
VL - 56
SP - 120
EP - 128
JO - IEEE Communications Magazine
JF - IEEE Communications Magazine
SN - 0163-6804
IS - 4
ER -