Consumer-Centric Sustainability: Empowering URLLC in Multi-UAV-Assisted MEC Systems for Industry 5.0

Consumer-centric energy-efficient 6G networks for Industry 5.0 are essential with the emergence of artificial intelligence and Internet of Things (AIoT) devices, necessitating ultra-reliable low-latency communication (URLLC) services. Moreover, multi unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) systems offer a promising solution to provide URLLC services in dynamic environments. However, they face significant challenges such as communication and trajectory design, high energy consumption, and reliability issues. Our paper introduces a novel approach to address these challenges by developing low-complexity intelligent optimization algorithms based on successive convex approximations (SCA). Our method aims to minimize the weighted sum energy consumption of ground AIoT devices and UAVs while satisfying the quality-of-service (QoS) requirements of URLLC. Simulation results demonstrate the superior performance of our proposed algorithms compared to standard fixed benchmark algorithms, achieving reduced energy consumption and optimizing UAV trajectories. This innovation enhances the sustainability and efficiency of multi-UAV-assisted MEC systems, facilitating the deployment of URLLC services in AIoT environments within consumer-centric energy-efficient 6G networks.