Age of Information minimization in UAV-aided data collection for WSN and IoT applications: A systematic review

The use of unmanned aerial vehicles (UAVs) for data gathering in wireless sensor networks (WSNs) and Internet of Things (IoT) applications has significantly gained interest in recent years. This shift is mainly attributed to the fast mobility and manoeuvrability of UAVs to deliver sensed data (by sensors and/or IoT devices) in remote, rural, or urban areas to the required destination (such as base stations or data centers). Age of Information (AoI) is a recent metric that measures the degree of freshness of information collected in data gathering applications, and in this context, data sensed by terrestrial sensing devices and transported by the UAV. Many researchers have thus focused on techniques to minimize AoI, mainly using machine learning and optimization methods. The research in this area is fast-growing, and some of the models studied are becoming more fine-grained, thus increasing the need for a comprehensive review of the proposed solutions, peculiar aspects, and diverse assumptions to draw lessons, identify challenges, and map out future considerations.

Review article

Oluwatosin Ahmed Amodu
Umar Ali Bukar
Raja Azlina Raja Mahmood
Chedia Jarray
Mohamed Othman

The use of unmanned aerial vehicles (UAVs) for data gathering in wireless sensor networks (WSNs) and Internet of Things (IoT) applications has significantly gained interest in recent years. This shift is mainly attributed to the fast mobility and manoeuvrability of UAVs to deliver sensed data (by sensors and/or IoT devices) in remote, rural, or urban areas to the required destination (such as base stations or data centers). Age of Information (AoI) is a recent metric that measures the degree of freshness of information collected in data gathering applications, and in this context, data sensed by terrestrial sensing devices and transported by the UAV. Many researchers have thus focused on techniques to minimize AoI, mainly using machine learning and optimization methods. The research in this area is fast-growing, and some of the models studied are becoming more fine-grained, thus increasing the need for a comprehensive review of the proposed solutions, peculiar aspects, and diverse assumptions to draw lessons, identify challenges, and map out future considerations.

Publication date
2023-07
Journal / proceedings
Journal of Network and Computer Applications
Publisher
Elsevier BV
Volume
216
Pages
103652
Article number
103652
DOI
10.1016/j.jnca.2023.103652

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Responsible AI & Scientific Computing
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Citation

Oluwatosin Ahmed Amodu; Umar Ali Bukar; Raja Azlina Raja Mahmood; Chedia Jarray; Mohamed Othman. 2023-07. Age of Information minimization in UAV-aided data collection for WSN and IoT applications: A systematic review. Journal of Network and Computer Applications. 103652. https://doi.org/10.1016/j.jnca.2023.103652

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1084-8045

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