The fifth generation (5G) of mobile networks will have to accommodate different types of use cases, each of them with different and stringent requirements and key performance indicators (KPIs). To support this, apart from novel technologies such as network slicing or artificial intelligence, 5G will require a flexible and efficient monitoring system. The collected metrics serve to optimize the performance of the network, and to confirm the achievement of the KPIs. Furthermore, in the envisioned multi-site, multi-stakeholder scenarios, having a common monitoring system is even more critical for an efficient optimization and service provisioning. In this paper, we present a Monitoring architecture for the distribution and consumption of metrics and KPIs for 5G multi-site platforms, where different verticals from different stakeholders are implemented over a shared infrastructure. We also assess the performance of the implemented publish-subscribe paradigm, to confirm that it suits the requirements of these scenarios, and discuss how the architecture could be mapped to other 5G scenarios.

The fifth generation (5G) of mobile networks is designed to accommodate different types of use cases, each of them with different and stringent requirements and key performance indicators (KPIs). To support the optimization of the network performance and validation of the KPIs, there exist the necessity of a flexible and efficient monitoring system and capable of realizing multi-site and multi-stakeholder scenarios. Nevertheless, for the evolution from 5G to 6G, the network is envisioned as a user-driven, distributed Cloud computing system where the resource pool is foreseen to integrate the participating users. In this paper, we present a distributed monitoring architecture for Beyond 5G multi-site platforms, where different stakeholders share the resource pool in a distributed environment. Taking advantage of the usage of publish-subscribe mechanisms adapted to the Edge, the developed lightweight monitoring solution can manage large amounts of real-time traffic generated by the applications located in the resource pool. We assess the performance of the implemented paradigm, revealing some interesting insights about the platform, such as the effect caused by the throughput of monitoring data in performance parameters such as the latency and packet loss, or the presence of a saturation effect due to software limitations that impacts in the performance of the system under specific conditions. In the end, the performance evaluation process has confirmed that the monitoring platform suits the requirements of the proposed scenarios, being capable of handling similar workloads in real 5G and Beyond 5G scenarios, then discussing how the architecture could be mapped to these real scenarios.

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