Experimenting with real application-specific
QoS guarantees in a large-scale RINA demonstrator
March 2018 – Septembre 2018
Fed4FIRE+ Open Call 3
Over the last several years, large research attention has been given to clean-slate network architectures for the Future Internet, capable of efficiently and effectively solving the well-known limitations of the current TCP/IP-based Internet architecture, e.g., in terms of routing scalability, application-specific Quality of Service (QoS) delivery or built-in security. In this context, the Recursive InterNetwork Architecture (RINA) has emerged as a very promising architectural solution to address these challenges. Such is the case, that a substantial number of European research projects have been funded to date to bring RINA closer to its eventual 5G market adoption (FP7 IRATI, FP7 PRISTINE, GEANT3+ Open Call IRINA, H2020 ARCFIRE).
To keep paving the way to this ambitious goal, large-scale experimental validations as enabled by the Fed4FIRE+ Federation of test-beds become of paramount importance. The present proposal for a medium experiment, ERASER, targets a larges-cale experimental evaluation of the real QoS guarantees that RINA can deliver to heterogeneous applications. A RINA test-bed composed of 87 nodes will be considered, emulating a 5G
metro/regional network scenario spanning from the end-user terminal until the virtual machines where applications run in a datacentre. To illustrate the QoS capabilities of RINA, we have chosen high-definition video streaming as our test application, for which the end-user quality of experience will be validated under different load conditions by injecting synthetic traffic in the network reproducing real application traffic.
Our experiments, never performed before nor in the roadmap of the currently running project H2020 ARCFIRE, will also shed light on the most appropriate deployments of the QoS policies in the recursive stack of layers (e.g., only at the bottom in the metro/regional network segment, or only at the top close to applications and end-users, or at all network layers), collecting measurements of the obtained QoS metrics for each deployment case.