Given the central role mobile core plays in supporting mobile network operations, the efficiency, cost-effective dynamic scalability and resilience of the core control plane are paramount. Achieving these goals, however, presents two main challenges: (i) decoupling core network state from processing; (ii) decoupling control plane processing in the core from its interface to the radio access network (RAN). To overcome them, we present CoreKube, a novel message focused and cloud-native mobile core system design, which features truly stateless workers (processing units) that interface with a common database (to hold the core network state) and with the RAN through a frontend. The fully stateless and generic nature of the workers to process any control plane message enables efficient message handling. Orchestration of containerized CoreKube components using Kubernetes, allows leveraging the latter's autoscaling and self-healing properties. We develop 4G and 5G standard-compliant CoreKube implementations, exploiting the agile development methodology enabled by CoreKube's message focused design. Results from our extensive experimental evaluations over the Powder platform relative to prior art show that CoreKube efficiently processes control plane messages, scales dynamically while using minimal compute resources and recovers seamlessly from failures.

Given the central role that the mobile core plays in supporting mobile network operations, the efficiency, cost-effective dynamic scalability and resilience of the core control plane are paramount. Achieving these goals, however, presents two main challenges: (i) decoupling core network state from processing; (ii) decoupling control plane processing in the core from its interface to the radio access network (RAN). To address these challenges, our proposed solution, CoreKube, is based on a novel message-focused and cloud-native design with truly stateless workers that interface with a common database (to hold the core network state) and with the RAN through a frontend in a standard compliant manner. The fully stateless and generic nature of the workers to process any control plane message enables efficient message handling. Orchestration of containerized CoreKube components using Kubernetes allows leveraging the latter's autoscaling and self-healing properties. This demo highlights three key features of CoreKube: dynamic scaling of core in the face of varying control plane traffic while maintaining low user-perceived latency, resilience to failures, and the ability to seamlessly interface with standard-compliant RAN and commodity hardware.

Given the wide interest on mobile core systems and their pivotal role in the operations of current and future mobile network services, we focus on the issue of their effective evaluation, considering the radio access network (RAN) emulation methodology. While there exist a number of different RAN emulators, following different paradigms, they are limited in their scalability and flexibility, and moreover there is no one commonly accepted RAN emulator. Motivated by this, we present Nervion, a scalable and flexible RAN emulator for mobile core system evaluation that takes a novel cloud-native approach. Nervion embeds innovations to enable scalability via abstractions and RAN element containerization, and additionally supports an even more scalable control-plane only mode. It also offers ample flexibility in terms of realizing arbitrary RAN emulation scenarios, mapping them to compute clusters, and evaluating diverse core system designs. We develop a prototype implementation of Nervion that supports 4G and 5G standard compliant RAN emulation and integrate it into the Powder platform to benefit the research community. Our experimental evaluations validate its correctness and demonstrate its scalability relative to representative set of existing RAN emulators. We also present multiple case studies using Nervion that highlight its flexibility to support diverse types of mobile core evaluations.

With the mobile networks evolving towards a software-based architecture with 5G, the research community has proposed several alternative core designs to address the issues recognized with the 4G core network architecture. It is notable, however, that these proposals are evaluated in bespoke ways which do not allow evaluate other proposals or even standard-compliant core networks, presenting several limitations in terms of the number of devices and the network load patterns that can be generated. To this end, we present Nervion, a cloud-native RAN emulator for scalable and flexible core network evaluations. Nervion leverages a compute cluster via containerization to emulate a large number of standard-compliant UEs and eNBs/gNBs generating workloads along both the control- and data-plane with a high degree of customization. This demo highlights the features of Nervion via the evaluation of a 5G core network and serves as a guide on how to use the public profile of Nervion on the Powder platform.