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ARCFIRE paper on Rumba accepted @ IEEE Infocom CNERT

A paper describing Rumba – the RINA experimentation automation framework – entitled  “Rumba: a Python Framework for AutomatingLarge-Scale Recursive Internet Experiments on GENI and FIRE+” has been accepted for presentation at the IEEE Infocom 2018 Workshop on CNERT (Computer and Network Experimental Research using Testbeds) in Hawai.  Congratulations to the iMec and Nextworks ARCFIRE teams!! Abstract A number


Addressing the serious challenges of next generation networks with an architectural approach

There are many challenges to achieve next generation networks. Many of the “marketed” benefits of 5G cannot be achieved unless the network allows new approaches to Security, End to End (E2E) Service Layers that are independent of lower layer resource allocation and guarantee Quality of Service (QoS). In fact ARCFIRE advisory board member Sue Rudd has gone one

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Two new ARCFIRE papers accepted @ IEEE/IFIP NOMS

Two papers on network management, entitled “Taming policy complexity: Model to execution” and “5G Networks Must Be Autonomic!” have been accepted for presentation at the IEEE/IFIP NOMS conference in Taipei. The first paper discusses a formal universal policy model for policy-based management that separates invariant parts from variant parts, while the second one presents a conceptual approach for modeling

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Paper on Distributed Mobility Management in RINA accepted @ IEEE WCNC 2018

A paper entitled “Mobility management in RINA networks:experimental validation of architectural properties” has been accepted for presentation at the IEEE WCNC 2018 conference in Barcelona. The paper discusses and validates experimentally the architectural properties of RINA that facilitate achieving scalable and efficient distributed mobility management across multiple networks. Abstract Mobility management is a challenging problem in current


Addressing common operations and maintenance problems in a fundamental way through RINA

What should be the main goal of any 5G architecture considering the network, service, and business, as well as operation, control and management. Is it to realise a largely self-governed network that adjusts its behaviour according to service requirements, business requirements, and instantaneous demand? I think those goals provide the frame for how the network


Application discovery and mobility demo @ IEEE NFV SDN

The first week of November ARCFIRE researchers enjoyed a couple of sunny days in Berlin attending the IEEE NFV SDN conference. ARCFIRE participated at the demo session, showing how RINA empowers the delivery of Multi-Access Edge Computing (MEC) use cases by supporting Distributed Mobility Management without tunnels, secure resource slicing, dynamic application discovery across layers


RINA research results presented at the SDN NFV World Congress 2017

Last week ARCFIRE researchers were present at the SDN & NFV World Congress 2017, in the context of the ETSI NGP Forum, one of the sessions within the conference. ARCFIRE researchers introduced RINA and discussed a number of research results achieved within the ARCFIRE and PRISTINE projects, in the areas of congestion control, dynamic renumbering, security,

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TADHack Global: ARCFIRE – RINA Rumba Winners

What a jam packed 2 weekends of application hacks over at TADHack Global. With locations Auckland, Brisbane, Melbourne, Singapore, Sydney, Islamabad its satellite Karachi, Kuala Lumpur, Kyiv, The Hague, Lagos, Lusaka, St Petersburg, Chicago, and Buenos Aires, on stream 23 – 24 September and Sri Lanka, Pune, Athens, London, Madrid, Paris, and Popayán on stream 29 September

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Paper on MEC demo using RINA accepted @ IEEE NFV SDN conference

A “demo” paper entitled “Open Multi-Access Edge Computing and Distributed Mobility Management with RINA” has been accepted for presentation at the IEEE NFV SDN conference in Berlin. The paper discusses how RINA can be leveraged to support Multi-Access Edge Computing (MEC) use cases. We’ll be presenting at the demo session, showing a demonstration of the whole system. Abstract MEC