Bibliographic Details
| Title: |
A Study on Multiple UAVs-based Divisive Hierarchical Clustering Scheme for Energy Efficiency and Uniform Latency in WSANs. |
| Authors: |
Xuan Zhang1,2, Heejung Byun3 heejungbyun@suwon.ac.kr |
| Source: |
Journal of Internet Computing & Services. Feb2025, Vol. 26 Issue 1, p1-7. 7p. |
| Subject Terms: |
*Energy consumption, Wireless sensor networks, Actuators, Internet of things, Wireless sensor nodes, Drone aircraft, Hierarchical clustering (Cluster analysis), K-means clustering |
| Abstract: |
In response to the harsh and limited conditions prevalent in remote areas, wireless sensor and actuator networks (WSANs) play an essential role in Internet-of-Things (IoT) systems by monitoring and interacting with unattended environments. Sensor nodes employed by the majority of WSANs are powered by batteries. Therefore, ensuring the efficient use and conservation of energy is vital for guaranteeing network connectivity. To address this challenge, we proposed a divisive hierarchical clustering method based on the K-means++ to organize the sensors nodes. We utilize Unmanned Aerial Vehicles (UAVs) for simultaneous data collection and develop a modified Improved Partheno Genetic Algorithm incorporating the Davies-Bouldin index for UAV scheduling. This approach effectively reduces network delay and balances network load. Numerical simulations demonstrate that our proposed method not only extends network lifetime but also balances energy savings and data collection latency. [ABSTRACT FROM AUTHOR] |
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| Database: |
Business Source Complete |
