TY - JOUR
T1 - An Aerial-Computing-Assisted Architecture for Large-Scale Sensor Networks
AU - Gu, Zhaoquan
AU - Li, Dongda
AU - Guizani, Nadra
AU - Du, Xiaojiang
AU - Tian, Zhihong
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/10/1
Y1 - 2021/10/1
N2 - Wireless sensor networks have been widely adopted in various areas. However, large-scale sensor networks face four critical problems. Information transmissions through the network would cause the energy hole problem; deploying sensors in a distributed manner might cause the isolated problem; simultaneous transmissions lead to the communication collision problem; and the lack of intelligent computing incurs the limited computation problem. Due to drones' high mobility and flexibility, drone-based aerial computing emerges as a new paradigm to address these problems. In this article, we propose an aerial-computing-assisted architecture for large-scale sensor networks; the core layer contains the following modules: Sensor localization, trajectory planning of drones, communication control between drones and sensors, and enabling intelligent computation on drones. The architecture significantly advances large-scale sensor networks with higher efficiency, smaller delay, larger lifetime, and more powerful computing capability.
AB - Wireless sensor networks have been widely adopted in various areas. However, large-scale sensor networks face four critical problems. Information transmissions through the network would cause the energy hole problem; deploying sensors in a distributed manner might cause the isolated problem; simultaneous transmissions lead to the communication collision problem; and the lack of intelligent computing incurs the limited computation problem. Due to drones' high mobility and flexibility, drone-based aerial computing emerges as a new paradigm to address these problems. In this article, we propose an aerial-computing-assisted architecture for large-scale sensor networks; the core layer contains the following modules: Sensor localization, trajectory planning of drones, communication control between drones and sensors, and enabling intelligent computation on drones. The architecture significantly advances large-scale sensor networks with higher efficiency, smaller delay, larger lifetime, and more powerful computing capability.
UR - http://www.scopus.com/inward/record.url?scp=85119972673&partnerID=8YFLogxK
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U2 - 10.1109/MWC.101.2100045
DO - 10.1109/MWC.101.2100045
M3 - Article
AN - SCOPUS:85119972673
SN - 1536-1284
VL - 28
SP - 43
EP - 49
JO - IEEE Wireless Communications
JF - IEEE Wireless Communications
IS - 5
ER -