Joint UAV deployment, SF placement, and collaborative task scheduling in heterogeneous multi-UAV-empowered edge intelligence

To support artificial intelligence (AI)-involved tasks offloaded from the mobile devices (MDs), it is necessary to equip the Unmanned Aerial Vehicle (UAV) with custom-made co-processor (CP) for handling AI workloads in multi-UAV-empowered Edge Intelligence. Existing CPU-oriented task scheduling algorithm cannot apply to the CPU+CP heterogeneous architecture. In this backdrop, this paper first formulates the joint service function placement, collaborative task scheduling, UAV deployment, and MD position determination problem as a Mixed Integer Non-Linear Programming problem. Then, an alternating optimization-based algorithm is put forward to derive a sub-optimal solution of the problem utilizing Differential Evolution and Greedy-based Hungarian algorithms. A series of experiments are conducted to evaluate the performance of the proposal. Results show that authors' proposal can achieve an overall revenue that is roughly 50% higher than those of existing methods.