移动边缘计算作为一个新兴架构，将云计算服务通过移动边缘计算服务器扩展到靠近用户的网络边缘，满足了需要实时控制和即时数据分析的应用需求。然而，由于移动边缘计算服务器的计算能力有限，导致任务的滞后时间较长。为了改善现状，本文提出了一种最小总滞后时间的调度算法，服务器确定任务计算的最优顺序以最小化总滞后时间。此外，本文还提出了一种激励机制，使得用户提交具有合理的计算量和预期完成时间的任务，同时在服务器计算资源不足时减少提交任务的数量和计算量。结果表明，该算法在接近传统调度算法性能的同时，在总滞后时间和平均滞后时间上提高了17%到200%。
As an emerging architecture, mobile edge computing extends cloud computing services to the edge of the network close to users through mobile edge computing servers, meeting the needs of appli-cations that require real-time control and real-time data analysis. However, due to the limited computing power of the mobile edge computing server, the delay time of the task is long. In order to improve the status quo, this paper proposes a scheduling algorithm with minimum total delay time. The server determines the optimal order of task calculation to minimize the total lag time. In addition, this paper also proposes an incentive mechanism that allows users to submit tasks with reasonable computational effort and expected completion time, while reducing the number and amount of submitted tasks when the server computing resources are insufficient. The results show that the proposed algorithm’s performance is close to the traditional scheduling algorithms, and increases 17% to 200% in total delay time and average delay time.