TNT 2023

2nd International Workshop on Technologies for Network Twins

co-located with IEEE-IFIP NOMS 2023 // 8-12 May 2023 // Miami, FL, USA

The goal of this event is to bring researchers and practitioners of digital twin technologies in networking together from across the globe.

Call for Papers

Digital twin in networking has seen a continuous and rising interest from the research, engineering, and operational communities in recent years, with proposals on base technologies, architectures, and practical implementations.

Digital twins provide virtual and real-time representations of physical infrastructures and empower network designers and operators to achieve simplified, automatic, evidence-driven, and resilient full life-cycle operation and maintenance.

Two aspects are emerging as important research topics for network digital twins: (1) how digital twin technologies enable new ways of managing and operating networks and digital infrastructures, and (2) how the network infrastructure itself can support and ease the development of large-scale digital twins systems by developing innovative forms of networked systems management and control. Federation, data fusion, interoperability, and integrability of heterogeneous network twins in multi-provider, multi-operator and multi-domains/multi-applications environments will become increasingly important to allow digital twin technologies to deliver their full potential and value across all industries.

The highly distributed and necessary collaborative nature of networking requires exploring, as a fundamental enabler, the mechanisms for building and programming distributed digital twin environments, supporting independent management domains via federation and other cooperative mechanisms. This essential feature would require specific data and knowledge sharing mechanisms, able to accommodate different topology patterns, and supporting open integration in environments with ever increasing sets of interrelated actors. Artificial Intelligence techniques and their innovative application in the networked infrastructure will become essential tools and enablers for managing the network and for supporting the deployment of digital twin applications from several industries.

The goal of the workshop is to offer an open forum to the various network management, operations, automation and softwarization communities and to outline the importance of these techniques for the future development of modern management and automation platforms. The workshop will explore recent advances in the field of network digital twins, comprising but not limited to:

  • Network digital twin reference architectures and design principles

  • Network digital twin enabling techniques such as (but not limited to) knowledge graphs, data fusion, graph neural networks, closed control loops, network modeling and visualization, modeling, languages, data collection and handling, network simulation framework, etc.

  • Network digital twins solutions applied in areas such as mobile network (e.g., digital twins for 5G, beyond-5G and 6G networks), transport networks, optical networks, data centers, etc. with particular reference to network digital twin use cases, experimentations, proof-of-concepts, report on field trials and real-world deployments

  • Network digital twins frameworks and solutions for supporting enterprise, smart-x, industrial IoT, including scenarios combining digital infrastructures and vertical industries. With particular interest to proof-of-concepts, use cases, experimentations, field trials and future deployments

  • Applicability of network digital twins to the full lifecycle of the network, such as design, planning, deployment, operation, maintenance, and optimization; considerations and possible enhancements to availability, resiliency, performance, trust, and security digital infrastructures with digital twins

  • Applicability and integration of artificial intelligence technologies for network digital twins. With particular interest to: (1) the generation of synthetic data (e.g., user and network traffic) with generative models such as Generative Adversarial Networks, (2) trustworthy and explainable AI (xAI) for network digital twins and their components and (3) ML components resilient to adversarial attacks

  • Network digital twin energy efficiency (“carbon-friendly” system)

  • Network digital twin programmability, comprising definition of interfaces and protocols used in network digital twin; recent developments in network digital twin standards, open source, and regulatory frameworks; network digital twins testing and interoperability frameworks and experiences; and Network digital twin implementations, tools, toolchains, automation, and operation platforms