An Aerial-Computing-Assisted Architecture for Large-Scale Sensor Networks

Zhaoquan Gu, Dongda Li, Nadra Guizani, Xiaojiang Du, Zhihong Tian

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)43-49
Number of pages7
JournalIEEE Wireless Communications
Volume28
Issue number5
DOIs
StatePublished - 1 Oct 2021

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