SPADE: Simulator-assisted Performability Design for UAV-based monitoring systems

Abstract

As Uncrewed Aerial Vehicles (UAV) have been used widely in a variety of real-world monitoring applications, quality design of UAV-based monitoring systems becomes an emergent challenge as it involves complex trade-offs among several performance criteria. While analytical models have been used for performance analysis of UAV systems, they often rely on hypothetical parameter values due to difficulty in accessing real-world systems, resulting in a gap between theory and practice. To fill this gap, this paper proposes SPADE (Simulator-assisted PerformAbility Design methodology for UAV-based Systems), an approach that integrates performance profiling with a realistic flight scenario generated by a UAV simulator and model-based performance analysis. We demonstrate the application of SPADE through a case study that focuses on designing a UAV-based ecological monitoring system using an object detection algorithm (YOLOv5). Our analysis explores key trade-offs among several quality metrics, including detection accuracy, performance, energy consumption, and service availability. Using Stochastic Petri Nets, we conduct numerical evaluations, with baseline parameter values estimated from performance profiling on an emulated computing device. Experimental results using YOLOv5 provide valuable insights into how image resolution and computation modes impact UAV-based system performance and availability. These findings offer practical guidance for improving UAV system design.