Service Function Chain Scheduling in Heterogeneous Multi-UAV Edge Computing

Supporting Artificial Intelligence (AI)-enhanced intelligent applications on the resource-limited Unmanned Aerial Vehicle (UAV) platform is difficult due to resource gap between two. It promising partition an AI application into a service function (SF) chain and then dispatch SFs onto multiple UAVs. However, it still challenging task efficiently schedule computation communication resources of UAVs support large number SF chains (SFCs). Under multi-UAV edge computing paradigm, this paper formulates SFC scheduling problem as 0–1 nonlinear integer programming problem. Then, two-stage heuristic algorithm put forward solve At first stage, if are surplus, SFCs deployed UAV servers in parallel based our proposed pairing principle for minimizing completion time sum tasks. In contrast, revenue maximization method adopted deploy arrived serial mode when insufficient. A series experiments conducted evaluate performance proposal. Results show that outperforms other benchmark algorithms tasks, overall revenue, execution success ratio