Abstract

The proliferation of the Internet of Things (IoT) has significantly impacted the integration of digital and physical realms, with Wireless Sensor Networks (WSN s) playing a crucial role. However, these sensor nodes often face challenges related to battery constraints and deployment in inaccessible terrains. The advent of Unmanned Aerial Vehicles (UAVs) presents a transformative solution, particularly for data collection from remote IoT devices. This work explores the application of UAV s to improve data collection in dense IoT sensor networks. We propose a novel approach called optimizing UAV-assisted data collection in IoT sensor networks using Dual Cluster Head (UAVDCH) that utilizes dual cluster heads within each cluster to optimize the UAV's energy consumption. The primary cluster head is responsible for collecting data within the cluster, while the secondary cluster head is tasked with transmitting the data to the UAV. Our objective is to maximize the available data the UAV collects with respect to its energy constraints. We develop a strategy for selecting appropriate secondary cluster heads, determining UAV's hovering points, and designing flight trajectories that maximize data collection. By adopting a multi-channel technique, we facilitate simultaneous data collection from multiple clusters, reducing hovering and transmission times. Experimental results demonstrate that our algorithm outperforms existing methods, offering a promising solution for energy-efficient data collection in IoT sensor networks.

Department(s)

Computer Science

Comments

National Science Foundation, Grant SCC-1952045

Keywords and Phrases

Clustering; Data collection; Dual-cluster heads; Flight trajectory; IoT; UAV

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Jan 2024

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