Reducing Temporal Interference in Private Clouds through Real-Time Containers

Providing innovative resource-efficient solutions able to mitigate temporal interference among cloud services, concurrently sharing the same underlying platform, is crucial to deploy highly time-sensitive applications at the edge of the network where resources are strongly restrained, and timing constraints are stringent. A notable example is provided by the allocation of virtualized network functions in the radio access network of modern mobile networks, such as 5G. This paper describes a kernel mechanism that can be applied to the design of an architecture providing fine-grain control of the temporal interferences among concurrent real-time services while avoiding overheads related to machine virtualization. On top of them, a model is proposed to meet the required end-to-end application performance through tuning of parameters in the underlying novel architecture. We show that theoretical latency/load curves match closely with experimental data gathered from a real implementation carried out using both a networking microbenchmark and a real IMS application.