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An experimental publish-subscribe monitoring assessment to Beyond 5G networks

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An Experimental Publish-Subscribe monitoring.pdf (550.7Kb)
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URI: http://hdl.handle.net/20.500.12761/985
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Author(s)
Pérez, Ramón; García-Reinoso, Jaime; Zabala, Aitor; Serrano, Pablo; Banchs, Albert
Date
2021-04-07
Abstract
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.
Share
Files
An Experimental Publish-Subscribe monitoring.pdf (550.7Kb)
Identifiers
URI: http://hdl.handle.net/20.500.12761/985
Metadata
Show full item record

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