关键词: 无人机配送, 移动边缘计算, 任务调度, 端边协同, 并行计算

Abstract: In the last-mile delivery scenario of Unmanned Aerial Vehicles (UAVs),the existing cloud computing architecture has a high latency problem,which cannot meet the execution requirements of artificial intelligence applications.The edge computing architecture can meet the needs of artificial intelligence applications by sinking computing resources to the edge with its low latency and high computing capabilities.However,most of the current researches are limited to a single edge server and lack the design of a parallel collaboration framework.According to the characteristics of MEC environment and the last mile of UAV delivery process,the computing load of edge server was fully considered and a multi-edge server parallel task processing framework was designed based on collaborative device and edge.The scheduling algorithm of Shortest Scheduling Latency First (SSLF) task was improved and α-SSLF algorithm was designed.The α-SSLF algorithm could fully consider optimizing task execution time under unstable network actual data rate.Experimental result showed that the proposed framework was superior to the traditional serial task processing framework in processing latency.

Key words: unmanned aerial vehicle delivery, mobile edge computing, task scheduling, collaborative device and edge, parallel computing