Periodic Reporting for period 2 - ARCFIRE (Large-scale RINA benchmark on FIRE)
Período documentado: 2017-01-01 hasta 2018-06-30
1. Compare the design of converged operator networks using RINA to state-of-the-art operator network designs.
2. Produce a robust RINA software suite; mature enough for large-scale deployments and long-lived experiments.
3. Provide relevant experimental evidence of RINA benefits for network operators, application developers and end-users.
4. Raise the number of organisations involved in RINA research, development and innovation activities.
5. Enhance FIRE+ as a platform for large-scale experimentation with RINA
With a total of eleven deliverables produced during the first reporting period, the ARCFIRE project has progressed with great strides. Through WP2 the project has analysed what technologies can be used today to design and implement a converged network vision following an all-IP approach, analysing its limitations in terms of network architecture; protocol design; naming, addressing and routing; mobility and multi-homing; quality of service, resource allocation, congestion control; security and network management [D21]. WP2 has also carried out the description of the design of a converted operator using RINA (number and type of DIFs, connectivity graph of each Distributed IPC Facility (DIF), policies of each DIF, network manager strategies), and a comparison with current operator designs at the architecture level [D22]. Moreover, it has also evaluated the potential value propositions of RINA for 5G and provided detailed discussions of important aspects for them.
In WP3 the ARCFIRE team has defined the procedures for development, fully automated testing and verification of the ARCFIRE software, based on the IRATI demonstrator. Starting from the code released by FP7 PRISTINE, the team has also focused on several improvements of the available RINA software (IRATI, DMS, rlite). WP3 has designed and partially implemented the ARCFIRE measurement and experimentation framework, with the goal of providing a powerful and easy-to-use tool for the WP4 activities.
By the work carried out by WP4, ARCFIRE has setup procedures for data management and established a Zenodo repository for data archiving. The project also surveyed and selected the testbed infrastructure available, most notably through the Fed4FIRE+ federation [D42]. Project experiments have created accounts on Fed4FIRE and are getting familiar with its tools. Finally, WP4 has developed detailed plans for each of its 4 planned experiments [D43].
WP5 has planned the projects dissemination [D52], standardisation and exploitation [D53] activities of the project, and started the execution of the ones relevant to the first year. Dissemination activities have been focused in preparing papers for conferences, RINA tutorials at scientific venues, demos and workshop at the SDN World congress, open source initiatives, internal partner dissemination events and engagement with the External Advisory Board. Standardisation activities have gravitated around the ISO SC6 WG7 on Future Networks, the ETSI ISG on Next Generation Protocols and the Pouzin Society.
5G has matured in a number of areas since the start of the ARCFIRE project. However, the complexity to define what a 5G network is, means that new concepts, architectures, and learnings do appear frequently. ARCFIRE is part of this dynamic environment, which creates a challenge in providing a future-proof and consistent report with added value that we can contribute back to the 5G R&D efforts.
ARCFIRE addresses this challenge by looking at new forces for operators such as disaggregating the radio access network, redefining the core network, and evolving the transport network. ARCFIRE takes two representative studies as basis to identify the facilitators of 5G, the goals set out be various stakeholders, the recommendations relevant to ARCFIRE, and the final challenge in that RINA and ARCFIRE are keen to address: automation.
ARCFIRE has brought forward and discusses an ideal RINA network in 5G. This discussion starts with general design considerations followed by detailed views for the access network, metro aggregation, and the core network. ARCFIRE looks at concrete 5G scenarios (radio access, cloud), autonomic control, and policy-based management (called strategies in RINA). It also provides a first look at advanced ARCFIRE work on RINA-inspired modelling for 5G operation and maintenance, such as a general resource abstraction model and adaptive policies (for higher level management strategies). Each part of this introduces a 5G concept (or scenario or challenge) and then details how RINA in general and ARCFIRE in particular can address it.
ARCFIRE then backs up these discussions with a view on ARCFIRE experiments and how they relate to the converged service provider network design discussed in D22. Such experiments will have immense impact on the networking community and 5G R&D.