Multi-access Edge Computing (MEC) is an enabling technology to leverage new network applications, such as virtual/augmented reality, by providing faster task processing at the network edge. This is done by deploying servers closer to the end users to run the network applications. These applications are often intensive in terms of task processing, memory usage, and communication; thus mobile devices may take a long time or even not be able to run them efficiently. By transferring (offloading) the execution of these applications to the servers at the network edge, it is possible to achieve a lower completion time (makespan) and meet application requirements. However, offloading multiple entire applications to the edge server can overwhelm its hardware and communication channel, as well as underutilize the mobile devices' hardware. In this paper, network applications are modeled as Directed Acyclic Graphs (DAGs) and partitioned into tasks, and only part of these tasks are offloaded to the edge server. This is the DAG application partitioning and offloading problem, which is known to be NP-hard. To approximate its solution, this paper proposes the FlexDO algorithm. FlexDO combines a greedy phase with a permutation phase to find a set of offloading decisions, and then chooses the one that achieves the shortest makespan. FlexDO is compared with a proposal from the literature and two baseline decisions, considering realistic DAG applications extracted from the Alibaba Cluster Trace Program. Results show that FlexDO is consistently only 3.9% to 8.9% above the optimal makespan in all test scenarios, which include different levels of CPU availability, a multi-user case, and different communication channel transmission rates. FlexDO outperforms both baseline solutions by a wide margin, and is three times closer to the optimal makespan than its competitor.

翻译：多接入边缘计算（MEC）作为一项使能技术，通过在网络边缘提供更快的任务处理能力，支撑虚拟现实/增强现实等新型网络应用。该技术通过在靠近终端用户的位置部署服务器来运行网络应用。这些应用通常具有任务处理密集、内存占用高、通信开销大等特点，导致移动设备可能耗费大量时间甚至无法高效运行。通过将应用执行任务迁移（卸载）至网络边缘服务器，有望降低完成时间（makespan）并满足应用需求。然而，将整个应用批量卸载至边缘服务器可能使其硬件及通信信道过载，同时导致移动设备硬件资源闲置。本文将网络应用建模为有向无环图（DAG）并分割成任务单元，仅将部分任务卸载至边缘服务器。此即DAG应用分割与卸载问题，已知属于NP-hard问题。为逼近最优解，本文提出FlexDO算法。该算法通过结合贪婪阶段与置换阶段生成一组卸载决策方案，并从中选取完成时间最短的方案。基于阿里集群追踪程序中的真实DAG应用数据，本文将FlexDO与文献方案及两种基准决策进行对比。实验结果表明，在所有测试场景（包括不同CPU可用性、多用户环境及不同通信信道传输速率）中，FlexDO的完成时间始终仅比最优值高3.9%至8.9%。FlexDO在性能上大幅超越两种基准方案，且其完成时间距离最优值的差距仅为对比方案的三分之一。