ABSTRACT
Abstract
This paper addresses malware-contaminated data collection in solar-powered IoT networks by equipping a UAV with a virtual network function for traffic inspection. A MILP jointly optimizes UAV placement and trajectory, data processing, channel allocation, and device energy use. For online operation, a neural-network mapping method stores integer decisions offline and retrieves them during flight, enabling fast linear-program refinement and reducing malware traffic reaching the gateway.