ARCFIRE’s D4.3 Design of experimental scenarios, selection of KPIs and metrics [pdf] is now available for download at the deliverables area.

This deliverable details the preparatory work done in ARCFIRE WP4 before the actual experimentation can begin. It takes the converged network operator scenarios for a traditional network design and the RINA designs that were developed in WP2 together with the testbed overview that was compiled by T4.1 and extracts interesting reference scenarios for the 4 main experiment objectives. This document will thus serve as a crutch for the experimenters during experimentation, providing all necessary information on the experiment objectives and tools in one location, and providing references to the sections of the WP2 deliverables where more details can be found.

Physical resources in one of the mobility management experiments

First, this document briefly summarises the WP2 reference scenarios for the converged network operator, focusing on the architecture of the access network, since that is where the technology diversification is most apparent. The first experiment will investigate the differences between a RINA and an evolutionary 5G network in terms of management complexity, targeting configuration management deploying a new service. The experiment has been divided into 4 sub-experiments with green and brown field starting points for the service. The second experiment will perform network performance oriented measurements, pitting a 5G scenario based on LTE vs a 5G scenario based on RINA. Here, ARCFIRE will evaluate network parameters such as overhead with respect to both data transport and mobility management, and scalability with respect to routing, also in the presence of network failures. The third experiment turns our sight towards multi-provider networks. RINA will be evaluated towards its capability for maintaining end-to-end QoS guarantees with respect to delay, jitter and bandwidth. Furthermore, it will evaluate how renumbering end-users addresses with respect to the location in the network improves overall scalability. Experiment 3 will also delve into the OMEC scenario for RINA, keeping applications reachable while they move through the network. The fourth and final experiment brings ARCFIRE in the world of DDoS attacks. It will investigate the various checks in RINA’s flow allocation can bar malicious attackers from taking down critical services.