Cluster-Based Age of Information Minimization in UAV-Assisted IoT Networks

Authors : Bilge Kagan Dedeturk, Nazlı Tekın

Pages : 973-984

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Publication Date : 2025-12-31

Article Type : Research Paper

Abstract :Unmanned Aerial Vehicles (UAVs) have attracted attention for collecting data in large-scale Internet of Things (IoT) networks. However, the Age of Information (AoI) minimization under energy constraints remains a computationally challenging problem. Although metaheuristic algorithms such as the Clonal Selection Algorithm (CSA) provide near-optimal solutions for sparse IoT networks, their scalability rapidly decreases with increasing numbers of IoT nodes in the network. To overcome this limitation, this work proposes a cluster-based method for scalable AoI minimization in UAV-assisted IoT networks. In the proposed approach, IoT nodes are clustered by using K-means clustering with optimal cluster size determination via the Silhouette Score method. Each cluster is solved independently using the CSA, and the results are merged to construct a global solution. This approach significantly reduces computational complexity while preserving the quality of the solution. Furthermore, parallel processing is used to optimize multiple clusters simultaneously. The results illustrate that the proposed cluster-based approach reduces the computation time by 90.54% compared to the baseline CSA while maintaining a comparable average AoI and energy efficiency. The method thus enables AoI-aware data collection in large-scale UAV-assisted IoT networks with hundreds of nodes.
Keywords : Bilgi Yaşı, İnsansız Hava Aracı, Nesnelerin İnterneti, Kümeleme, Klonal Seçim Algoritması, Meta-sezgisel Algoritmalar

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