The ultimate objective of the programmable networking research by TNO is to create a self-optimizing network service infrastructure, based on open networking and cloud technology. In this research project we make a step towards this long-term objective by investigating state-of-the-art the programmable network telemetry and its application to monitor and optimize end-to-end performance of advanced network services. Specifically, the objective is to create a system to collect and integrate telemetry data from the network, from the cloud systems hosting applications and – if possible – from the applications themselves.
As a specific use case for applying programmable end-to-end performance telemetry, we select eXtended Reality (XR) services. XR services are known to be highly demanding both from network (e.g., high bandwidth demand, low jitter) and processing perspective (e.g., transcoding latency).
In our talk we will discuss the architecture of the eXtended Reality system, developed in TNO SocialXR programma, instrumented in this project with various telemetry functions. We will touch upon network, cloud and application monitoring. We will present both successful developments as well as the difficulties that required workarounds or even problems that we could not solve. Finally, we will mention on how collected telemetry data is envisioned to be linked to the XR Quality of Experience.