KRS: Kubernetes Resource Scheduler for resilient NFV networks

To address the diversity of use cases envisioned by the 5G technology, it is critical that the design of the future networks allows maximum flexibility and cost effectiveness. This requires that network functions should be designed in a modular fashion to enable fast deployment and scalability. This expected efficiency can be achieved with the cloud native paradigm where network functions can be deployed as containers. Virtualization tools such as Kubernetes [1] offer multiple functionalities for the automatic management of the deployed containers hosting the network functions. These tools such as resource scheduling and replicas must be applied efficiently to improve the network functions availability and resilience. This paper focuses on resource allocation in a Kubernetes infrastructure hosting different network services. The objective of the proposed solution is to avoid resource shortage in the cluster nodes while protecting the most critical functions. A statistical approach is followed for the modeling of the problem as well as for its resolution, given the random nature of the treated information.