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Nokia, Inria extend research partnership to address future challenges facing networks and distributed computing | VanillaPlus

Paris, France – Nokia and Inria has announced the renewal of their joint research laboratory for the next four years. The new phase was launched at an event in Paris on November 14 in the presence of Thierry Klein, president, Nokia Bell Labs Solutions Research, and Bruno Sportisse, CEO of Inria.

Launched in 2008, the joint research laboratory brings together permanent scientists from the two partners with a newly created pool of doctoral and postdoctoral scientists, with the strategic aim of solving the main scientific challenges related to the evolution of networks and networked applications. The focus of the joint research is on the benefits of networked and distributed resources for contextual and personalized experiences in the digitally connected world.

Future networks will need to connect digital, physical and human worlds to unleash the innate potential of humans in the metaverse age. Networks will need to have the ability to optimize for a very wide range of customer-specific needs, for example in industrial applications. The network will develop enhanced discovery capabilities and greater context awareness in terms of user state and intent, dynamically and automatically adapting connectivity to user needs.

The networks will be 100% cloud native and support a distributed architecture. Efficiency, resiliency and agility are critical attributes, with zero-touch management and orchestration achieved through artificial intelligence (AI) and machine learning (ML)-driven autonomy. Devices may not be able to meet all computing needs and will rely on a combination of edge cloud and local near-device computing, resulting in a massively distributed computing architecture. Diversified applications and services will have stringent quality requirements, enabled by data/AI-native networks in a highly distributed computing and data environment.

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The collaboration between Nokia Bell Labs and Inria will contribute to solving these challenges by addressing three aspects:

  • Distributed learning over 6G: with the aim of enabling diverse AI applications that operate in a distributed and cooperative manner across the entire system (core, network, edge, device), constantly learning and evolving.
  • AI-Based Smart Network Management: aiming to provide analytics and reliable AI/ML for 5G advanced and 6G zero-touch mobile network management.
  • Network-aware industrial applications: with the aim of optimizing and adapting industrial applications, such as cloud-based robotic applications based on network performance and availability.

Thierry Klein, president of Nokia Bell Labs Solutions Research, said: “Inria and Nokia Bell Labs have had a rich and fruitful relationship for more than 20 years. Inria is part of the Bell Labs Distinguished Academic Partners program, which brings together the best and brightest minds from the world’s top universities and academic organizations to partner with us to transform human existence. This new phase of our partnership addresses the strategic challenges of the future infrastructure and applications of the digitally connected world, and we are excited about the collaborative benefits of this continued collaboration for Nokia, our industry and society to deliver enhanced experiences in a digitized world. make possible.”

Bruno Sportisse, CEO of Inria, said: “Nokia Bell Labs is one of our most important strategic partners and I am pleased that we are strengthening our partnership. For Inria, working with a global leader with a European footprint, such as Nokia, is one of our priorities, whether it’s positioning key science topics, maintaining joint scientific and technological excellence, or making an impact at scale of our work. The gradual evolution of our partnership also demonstrates the importance of building long-term relationships based on trust, within a shared strategy and roadmap. Together with Nokia, we will work on the new frontiers for 6G mobile networks, which bring new technological and theoretical challenges, where software design and data exchange must be tackled together.

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