The leitmotiv of ARCFIRE is to experimentally demonstrate at large scale they key benefits of RINA, leveraging former EC investments in Future Internet testbeds (FIRE+) and in the development of the basic RINA technology (IRATI, PRISTINE). ARCFIRE’s contribution will i) showcase the benefits and viability of RINA via large-scale experimental deployments; ii) quantify those benefits by comparing RINA with current Internet technologies using different Key Performance Indicators (KPIs) and iii) motivate the academic and industrial computer networking research communities to engage in RINA research, development and innovation activities. ARCFIRE will address the following specific objectives:

  • Compare the design of converged operator networks using RINA to state-of-the art operator network designs. ARCFIRE will analyse the design of current state of the art converged operator networks, carry out an equivalent design using RINA and compare both approaches using a set of KPIs.
  • Produce a robust RINA software suite; mature enough for large-scale deployments and long-lived experiments. IRATI, the most ambitious RINA implementation to date, is today mature enough to support short-lived experiments that allow only minor traffic variations in the range of a few hours (2-3) with a relatively small number of systems (up to 20), supporting only a couple of DIF levels. ARCFIRE will improve the open source IRATI software suite so that it is possible to make large-scale experimental deployments with up to 100 nodes (physical or virtual), supporting tens to hundreds of DIFs, up to 5 levels deep, running experiments for up to a week. These metrics will allow the IRATI implementation to be used both for rich experimental research activities and for internal trial deployments by network operators.
  • Provide relevant experimental evidence of the RINA benefits for network operators, application developers and end-users. ARCFIRE, via its WP4, will perform four extensive experiments with the goal of experimentally evaluating different aspects of converged RINA operator networks: T4.2 will look at the benefits of RINA when managing multiple layers over multiple access technologies; T4.3 will assess how RINA improves the operation of resilient, virtualised services over heterogeneous physical media; T4.4 will analyse end-to-end service provisioning across multiple RINA network providers and T4.5 will study the effectiveness of RINA against Distributed Denial of Service Attacks (DDoSs). All experiments will target large-scale deployments and run for relatively long periods of time (as defined in Objective 2).
  • Raise the number of organisations involved in RINA research, development and innovation activities. ARCFIRE will implement a set of actions in order to raise the acceptance of RINA by the computer networking research community. These actions are designed to overcome two of the main reasons for the current low number of researchers involved in RINA R&D: facilitate the understanding of the RINA concepts and mechanics and disseminate experimental results that prove the benefits of RINA in high-impact scientific publications and conferences.
  • Enhance FIRE+ as a platform for large-scale experimentation with RINA. Facilitate experiments with the IRATI RINA implementation on the FIRE+ facilities by documenting all the experiments carried out by the consortium using the FIRE+ infrastructure, publishing all the configurations and Virtual Machine (VM) templates used in those experiments and adapting or extending the generic FIRE+ experiment provisioning, control and monitoring tools. ARCFIRE will also provide feedback on these tools with respect to join FIRE+-GENI experiments.