The goal of NETWIN is to leverage the synergism between artificial intelligence and networks in two directions:

  • design machine learning strategies that will guide the design of autonomous networks able to efficiently handle the complexity of the telecommunications of the future with minimum human intervention;
  • design network architectures able to promote the pervasive deployment of delay-sensitive and energy-constrained intelligent services.

The project promotes also a paradigm shift from conventional Shannon-based approach, fundamentally concerned about the recovery of each transmitted bit, to a goal-oriented semantic framework, where the focus is on the recovery of the semantics underlying the transmitted message, within a goal-oriented design.
Special attention is posed on distributed machine learning strategies, running in the edge cloud, to provide delay-sensitive services with minimum energy consumption. The project includes the application of the developed novel methodologies to three use cases: aerial-assisted intelligent services, cooperative robots exploiting extended perception capabilities enabled by the edge cloud, and AI-aided extended reality.

Netwin is parte of Spoke: 8 – Intelligent and Autonomous Systems

Project PI: Sergio Barbarossa

  • The first collaborative effort of NETWIN has been the identification of the main scenarios of interest and the relative architectures. The results of this activity have been collected in the first milestone, produced at the end of June 2023.
  • NETWIN proposed novel architectures for semantic and goal-oriented communications, in order to identify and transmit only what is relevant, at the receiver side, to recover what is the semantics of the transmitted message, taking explicitly into account the goal of communication.
  • NETWIN focused also on fully automated zero-touch network architectures, with special attention to the 5G core network (5GC), working on the experimental validation of the theoretical results obtained in the first phase of the project, focusing on the implementation of microservice applications in the edge cloud.
  • NETWIN worked on distributed learning mechanisms, to be implemented in the edge cloud, with the goal of enabling low latency services and improving network efficiency.
  • Innovative semantic communication architectures, based on deep generative models such as variational autoencoders and probabilistic diffusion models
  • Implementation of microservice applications in the edge cloud using multi-cluster Kubernetes
  • Assessment of benefits of using AI models to optimize the transmission power, channel selection, and other parameters of the PHY and MAC layer
  • A new cloud network flow model for the optimization of microservice applications valid for arbitrary network topologies and able to accurately compute end-to-end service latency
  • Service placement and request routing including disaggregation of services and network functionalities
  • Multi-agent reinforcement learning techniques for dynamic control policies to be used for delay-constrained routing of delay-sensitive applications
  • Novel multi-sensor learning-based architectures for cooperative prediction and inference in partially unknown dynamical systems over sensor networks


The first demonstrator has been implemented and tested. It consists of a mobile robot that is endowed with intelligent capabilities thanks to computation offloading from the robot to the edge cloud, exploiting seamless integration of multiple radio access technologies (millimeterwaves at 60 GHz WiFi and sub-6 GHz 5G) and cloud/edge

resources. The testbed leverages Kubernetes, Istio service mesh, OpenFlow, public 5G networks, and IEEE 802.11ad mmWave (60 GHz) Wi-Fi access points. The architecture is validated through a use case in which a ground robot autonomously recognizes and follows a moving object by using an artificial intelligence-driven computer vision application. Computationally intensive navigation tasks are offloaded by the robot to microservice

instances, which are executed on demand within cloud and edge data centers that the robot can exploit during its journey.

Papers:
Giuseppe Baruffa; Andrea Detti; Luca Rugini; Francesco Crocetti; Paolo Banelli; Gabriele Costante; Paolo Valigi, “AI-Driven Ground Robots: Mobile Edge Computing and mmWave Communications at Work”, IEEE Open Journal of the Communications Society, 2024 

Francesco Binucci; Paolo Banelli; Paolo Di Lorenzo; Sergio Barbarossa, “Opportunistic Information-Bottleneck for Goal-Oriented Feature Extraction and Communication”, IEEE Open Journal of the Communications Society, 2024 

Sergio Barbarossa; Danilo Comminiello; Eleonora Grassucci; Francesco Pezone; Stefania Sardellitti; Paolo Di Lorenzo, “Semantic Communications Based on Adaptive Generative Models and Information Bottleneck”, IEEE Communications Magazine, 2023 
Fastweb and Logogramma just joined the project to contribute to the development of the proof-of-concept on AI-aided extended reality services.
Program partners: Cascade calls partners:
  • Dr. Eleonora Grassucci submitted a proposal for a Special Session at ICASSP 2024, Seoul, South Korea, entitled “Generative Semantic Communication: How Generative Models Enhance Semantic Communications”, that has been accepted.
  • Prof. Antonia Tulino gave a plenary talk entitled “A service-driven network evolution: from communication, to content distribution, to ubiquitous computation’’, at the IEEE International Symposium on Information Theory, June 30th, 2023.
  • Prof. Sergio Barbarossa gave an Invited talk entitled "Semantic and Goal-Oriented Communications: From Adaptive Generative Models to Optimal Resource Allocation", at the Huawei Strategy and Technology Workshop, Munich, Oct. 26th, 2023.
The main challenge of Netwin project is to bring Artificial Intelligence (AI) algorithms within the network design, with a twofold objectives:
1) make the networks more efficient thanks to additional capabilities in predicting behaviors and then allocate networks resources, radio, computation and storage, in an intelligent way;
2) use pervasive deployment of radio access points to bring intelligent services as close as possible to the end-user in order to promote delay-critical applications.

The project is also promoting a paradigm shift towards next-generation (6G) networks, exploiting generative AI algorithms to design innovative semantic and goal-oriented communications, where the idea is to transmit only the data that are necessary at the receiver side to generate a message that is semantically equivalent to the transmitted one, while not being necessarily identical at the bit level. This new perspective provides many additional degrees of freedom that can be exploited to make the overall transmission system more efficient. The first proof-of-concept prototype that has been implemented within the first half of the project is illustrative of the capability of the new design bring intelligent services in a mobile robot, with negligible delays due to task offloading mechanisms, thanks to the seamless integration of multiple radio access technologies (multi-RAT) and cloud/edge resources, unifying distributed and heterogeneous computing and communication resources into a cohesive continuum system, tailored for mobile applications
  1. Publications
    • Expected: >= 36 publications in 36 months
    • Accomplished: 18 (7 journal publications + 11 conference publications)
    • Readiness: 100%
  2. Joint Publications
    • Expected: >=12 (30% joint publications in 36 months)
    • Accomplished: 0
    • Readiness: 0% (joint collaborations have just started, joint publications will follow)
  3. Talks/Communication events
    • Expected: 10 talks or event chairing/organizing within NETWIN activities in 36 months
    • Accomplished: > 10 (6 invited talks, 1 special session at IEEE ICASSP 2024, 2 talks at RESTART General Meetings, and 11 conference presentations)
    • Readiness: >100%
  4. Demo/PoC
    • Expected: 3 PoCs expected by the end of the project
    • Accomplished: 0
    • Readiness: 0% (activity started only in March, with the inclusion of new partners that joined the consortium through the cascade calls)
  5. Project Meetings
    • Expected: > 12 meetings
    • Accomplished: 5 plenary project meetings + several WP meetings
    • Readiness:100%
  6. Patents/Innovations
    • Expected: 4 items over 36 months
    • Accomplished: 0 items submitted to mission 7
    • Readiness: 0%
M1.1- Scenarios and Architectures - Intermediate report First report on identification of use cases
30/06/23 achieved

M2.1- Semantic and goal-oriented communications - Intemediate report Definition of semantic network architectures, development of algorithms for joint semantic encoding/decoding using generative models
31/12/23 achieved

M3.1- Intelligent services for communications - Intermediate report Development and test of preliminary algorithms aimed at introducing machine learning algorithms for network control
31/01/24 achieved

M4.1- Distributed delay-sensitive intelligent services - Intermediate report Development and test of preliminary algorithms for distributed learning in the edge cloud 28/02/24 achieved
  • Expected: 4
  • Accomplished: 4
  • Readiness level: 100%

Researchers involved: Before the cascade call, the project was composed of 6 partners, involving in total 37 researchers. After the cascade call, additional 8 partners have joined the project with 32 more researchers.

Collaboration proposals
Given its methodological imprint, NETWIN is fully open to collaborations and it has already identified the following collaborations with other two other RESTART projects: 6GWINET and SUPER.
In the first phase of the project, NETWIN has collaborated with Spoke 8 to develop a joint strategy for the acquisition of instrumentations to be used for the project, such as a private 5G network. Furthermore, NETWIN has worked with Spoke 8 to set up the cascade calls useful to include new partners having specific expertise on the technologies involved in NETWIN proofs of concept.

For any proposal of collaboration within the project please contact the project PI.

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