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 solutions, considering realistic DAG applications extracted from the Alibaba Cluster Trace Program. FlexDO results are 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. It achieves up to 87% similarity with the optimal decision and does not burden the edge server.

多接入边缘计算 (MEC) 是一种通过在网络边缘提供更快的任务处理来利用虚拟/增强现实等新网络应用的支持技术。这是通过部署更靠近最终用户的服务器来运行网络应用程序来完成的。这些应用程序通常在任务处理、内存使用和通信方面非常密集；因此，移动设备可能需要很长时间甚至无法有效地运行它们。通过将这些应用程序的执行转移（卸载）到网络边缘的服务器，可以实现较低的完成时间（makespan）并满足应用程序要求。然而，将多个完整应用程序卸载到边缘服务器可能会压垮其硬件和通信通道，并且无法充分利用移动设备的硬件。在本文中，网络应用程序被建模为有向无环图（DAG）并划分为任务，并且只有部分任务被卸载到边缘服务器。这就是 DAG 应用程序分区和卸载问题，已知该问题是 NP 困难的。为了近似其解决方案，本文提出了FlexDO算法。FlexDO 将贪婪阶段与排列阶段相结合，以找到一组卸载决策，然后选择实现最短完工时间的决策。FlexDO 与文献中的提案和两个基准解决方案进行了比较，考虑了从阿里巴巴集群跟踪计划中提取的实际 DAG 应用程序。在所有测试场景中，FlexDO 结果始终只比最佳完工时间高出 3.9% 到 8.9%，其中包括不同级别的 CPU 可用性、多用户情况和不同的通信通道传输速率。FlexDO 的性能大幅优于这两种基准解决方案，并且比竞争对手更接近最佳完工时间三倍。它与最优决策的相似度高达 87%，并且不会给边缘服务器带来负担。