Container-based operation system (OS) level virtualization has been adopted by many edge-computing platforms. However, for an edge server, inter-container communications, and container management consume significant CPU resources. Given an application composed of interdependent tasks, the number of such operations is closely related to the dependency between the scheduled tasks. Thus, to improve the execution efficiency of an application in an edge server, task scheduling and task containerizing need to be considered together. To this end, a joint task scheduling and containerizing (JTSC) scheme is developed in this article. Experiments are first carried out to quantify the resource utilization of container operations. System models are then built to capture the features of task execution in containers in an edge server with multiple processors. With these models, joint task scheduling and containerizing is conducted as follows. First, tasks are scheduled without considering containerization, which results in initial schedules. Second, based on system models and guidelines gained from the initial schedules, several containerization algorithms are designed to map tasks to containers. Third, task execution durations are updated by adding the time for inter-container communications, and then the task schedules are updated accordingly. The JTSC scheme is evaluated through extensive simulations. The results show that it reduces inefficient container operations and enhances the execution efficiency of applications by 60 percent.

中文翻译：

---

联合任务调度和容器化以实现高效边缘计算


基于容器的操作系统（OS）级虚拟化已被许多边缘计算平台采用。然而，对于边缘服务器来说，容器间通信和容器管理会消耗大量的 CPU 资源。给定一个由相互依赖的任务组成的应用程序，此类操作的数量与计划任务之间的依赖关系密切相关。因此，为了提高边缘服务器中应用程序的执行效率，需要同时考虑任务调度和任务容器化。为此，本文开发了联合任务调度和容器化（JTSC）方案。首先进行实验来量化容器操作的资源利用率。然后构建系统模型来捕获具有多个处理器的边缘服务器中的容器中任务执行的特征。利用这些模型，进行联合任务调度和容器化如下。首先，任务的调度没有考虑容器化，这导致了初始调度。其次，基于从初始调度中获得的系统模型和指南，设计了几种容器化算法来将任务映射到容器。第三，通过添加容器间通信的时间来更新任务执行持续时间，然后相应地更新任务调度。 JTSC 方案通过广泛的模拟进行评估。结果表明，它减少了低效的容器操作，并将应用程序的执行效率提高了60%。