Applications that use edge computing and 5G to improve response times consume both compute and network resources. However, 5G networks manage only network resources without considering the application's compute requirements, and container orchestration frameworks manage only compute resources without considering the application's network requirements. We observe that there is a complex coupling between an application's compute and network usage, which can be leveraged to improve application performance and resource utilization. We propose a new, declarative abstraction called AppSlice that jointly considers the application's compute and network requirements. This abstraction leverages container management systems to manage edge computing resources, and 5G network stacks to manage network resources, while the joint consideration of coupling between compute and network usage is explicitly managed by a new runtime system, which delivers the declarative semantics of the app slice. The runtime system also jointly manages the edge compute and network resource usage automatically across different edge computing environments and 5G networks by using two adaptive algorithms. We implement a complex, real-world, real-time monitoring application using the proposed app slice abstraction, and demonstrate on a private 5G/LTE testbed that the proposed runtime system significantly improves the application performance and resource usage when compared with the case where the coupling between the compute and network resource usage is ignored.
翻译:使用边缘计算和 5G 来改进响应时间的应用会消耗计算和网络资源。 然而, 5G 网络只管理网络资源而不考虑应用程序的计算要求, 集装箱管弦框架只管理计算资源而不考虑应用程序的网络要求。 我们注意到, 应用程序的计算和网络使用之间有一个复杂的组合, 可以利用这种组合来改善应用程序的性能和资源利用。 我们提议了一个名为 Apptionsclic 的新、 宣示性抽象, 联合考虑应用程序的计算和网络需求。 这个抽象化利用集装箱管理系统来管理边缘计算资源和网络资源, 5G 网络堆管理网络资源, 由一个新的运行时间系统来明确管理计算和网络使用之间的合并考虑, 由新的运行时间系统来提供应用程序切片的宣示性语义。 运行时间系统还共同管理边缘计算和网络资源使用, 使用两种适应性算法来共同考虑应用程序的计算和网络需求。 我们应用一个复杂、 现实世界、 实时监测应用程序来管理边缘计算资源, 管理网络资源资源资源资源资源资源使用 管理, 并在私人 5G/ LTE 测试运行时, 系统进行显著的运行时, 模拟运行运行运行系统将大大改进资源使用。