Age of Information minimization for secure data collection in multi UAV-assisted IoT applications

Unmanned Aerial Vehicles (UAVs) have emerged as a promising solution for data collection in Internet of Things (IoT) applications, particularly in scenarios where traditional infrastructure is unavailable or unreliable. Minimizing the Age of Information (AoI) while providing secure data collection is crucial for delay-sensitive applications. However, secure data collection introduces considerable energy and delay overhead for both resource-constrained IoT devices and UAVs. This paper proposes a novel mixed integer programming (MIP) model to minimize the average AoI with the minimum number of UAVs. Unlike previous works that largely disregard the costs of security and energy constraints of IoT, the proposed model integrates the delay and energy costs of encryption methods on both UAVs and IoT devices. Colonial Selection Algorithm (CSA) is developed as a metaheuristic to overcome the computational complexity of the MIP model in large-scale IoT applications. The impact of attribute-based encryption (ABE) methods, such as Key-Policy ABE (KP-ABE) and Ciphertext-Policy ABE (CP-ABE), on AoI minimization and the minimum number of required UAVs is analyzed. The results demonstrate that the KB-ABE-YCT method performs better in minimizing AoI with fewer UAVs.