Clustered data muling in the internet of things in motion
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Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
This paper considers a case where an Unmanned Aerial Vehicle (UAV) is used to monitor an
area of interest. The UAV is assisted by a Sensor Network (SN), which is deployed in the area such as
a smart city or smart village. The area being monitored has a reasonable size and hence may contain
many sensors for efficient and accurate data collection. In this case, it would be expensive for one UAV
to visit all the sensors; hence the need to partition the ground network into an optimum number of
clusters with the objective of having the UAV visit only cluster heads (fewer sensors). In such a setting,
the sensor readings (sensor data) would be sent to cluster heads where they are collected by the UAV
upon its arrival. This paper proposes a clustering scheme that optimizes not only the sensor network
energy usage, but also the energy used by the UAV to cover the area of interest. The computation
of the number of optimal clusters in a dense and uniformly-distributed sensor network is proposed
to complement the k-means clustering algorithm when used as a network engineering technique in
hybrid UAV/terrestrial networks. Furthermore, for general networks, an efficient clustering model
that caters for both orphan nodes and multi-layer optimization is proposed and analyzed through
simulations using the city of Cape Town in South Africa as a smart city hybrid network engineering
use-case.
Description
Keywords
Clustering, Hybrid network, Computer security, Computer science, South Africa
Citation
Tuyishimire, E. et al. (2019). Clustered data muling in the internet of things in motion. Sensors ,19(3), 484. https://doi.org/10.3390/s19030484