Poster: Towards Constraint-Based Model Repair to Ensure Multiple Mission Objectives in UAV-Enabled MEC Systems for Disaster Response and Rescue

In recent years, the rapid advancement of Unmanned Aerial Vehicle (UAV) technology, combined with their aerial capabilities and versatility, has led to an increased deployment of UAVs in Multi-Access Edge Computing (MEC) environments. This is particularly evident in critical applications such as emergency disaster response, where the reliable operation of UAVs can significantly impact outcomes of safety-critical impacts. Given the high-stakes nature of these applications, ensuring the correctness and reliability of system design is very crucial. However, ensuring such reliability presents substantial challenges, particularly when a single task involves multiple concurrent objectives, or when new objectives emerge to address unforeseen issues within a system designed for specific goals.Motivated by this, our work proposes a formal approach which provides a constraints-based repair for system models of UAV-assisted MEC applications. Our approach first presents a general approach for modeling the system of UAV-assisted MEC applications using Markov decision process or continuous-time Markov chains. Then, our approach aims at developing a set of model repair algorithms for assuring the system model satisfying multiple mission objectives simultaneously. We demonstrated our approach through a case study focused on a UAV-assisted MEC system designed for disaster emergency rescue.