6th International Workshop on Intent-based Networking (WIN 2026)
Intent Based Networking (IBN) focuses on technology-agnostic, flexible and robust interactions between network infrastructure management and operating systems and their users. One of the main goals of IBN is the lifecycle automation and deployment acceleration of communication services and applications. As such, IBN articulates various mechanisms to recognize, understand, augment and refine intents based on service and operational requests.
Intent-based systems continuously strive to fulfill and assure service and network operation within the expected qualitative and performance boundaries, thanks to reliable system feedback.
The concept of IBN appeared in the 2010’s with a focus on automated policy configuration. IBN now reaches out to versatile applications and services deployed over heterogeneous digital communication infrastructures. A core challenge of IBN solutions is the stretch between generalization of the application scope (potentially spanning horizontally and vertically end-to-end through networks) and the need to run in a well-defined network scope and associated knowledge domains, while preserving enough flexibility.
The goal of this workshop is to gather research and experiments from industry, academia, standards and open-source works, to get a sense of IBN technology maturity, areas that require further exploration, development and validation. To this end, the workshop will cover IBN aspects of all domains including applications, concepts, lifecycle, challenges, architectures, modeling, instantiation, robustness, etc.
Topics of interest include and are not limited to:
● IBN concepts, architectures, and frameworks
● IBN enabling techniques: knowledge graphs, natural languages understanding, policy refinement, feedback control loops, smart telemetry, etc.
● IBN support by machine learning and artificial intelligence
● IBN applications and use cases, including scenarios combining digital infrastructures and vertical industries
● IBN proof-of-concepts, experimentations; report on field trials and real-world deployments
● IBN and digital twins
● IBN implementations, tools, and user interface design
● IBN applications for 5G, 5G-Advanced and 6G networks
● IBN and cybersecurity
● Enabling technologies for IBN: Generative AI and Large Language Models (LLM)
● IBN and VANETs
● Intent modeling, representation, languages, and intent translation techniques
● Intent and intent-related information models (policies and services)
● Intent recognition, recommendation, and abstraction techniques
● Intent assurance and assessment
● Availability, resiliency, performance, trust, and security considerations in IBN
● Interfaces and API for intent-based systems
● Recent advances on IBN in standards and open source
Submission Guidelines
Authors are invited to submit novel contributions, which are not under review in any other conference or journal, to: https://edas.info/N35282
Technical papers must be formatted using the IEEE 2-column format and not exceed 7 pages (including references).
Accepted papers will be included in NoF 2026 proceedings and indexed in IEEEXplore library.
Important dates
- Workshop paper submission deadline: July 11, 2026
- Workshop paper acceptance notification: August 15, 2026
- Camera-ready paper submission deadline: August 15, 2026
- Workshop date: September 29 or October 02, 2026
Technical Program Committee
- Anubhab Banerjee Nokia, Germany
- Davide Berardi Universitas Mercatorum, Italy
- Davide Borsatti University of Bologna, Italy
- Marc Bruyère Institute of Innovation Research Lab, Japan
- Chiara Contoli University of Urbino “Carlo Bo”, Italy
- Venkata Suman Doma USA
- Molka Gharbaoui Scuola Superiore Sant’Anna, Italy
- Jaehoon (Paul) Jeong Sungkyunkwan University, South Korea
- Andreas Johnsson Ericsson Research, Sweden
- Koteswararao Kondepu Indian Institute of Technology Dharwad, India
- Danny Alex Lachos Perez BENOCS GmbH, Germany
- Sandor Laki Eötvös Loránd University, Hungary
- Diego Lopez Telefonica, Spain
- Gurundha Mangalampenta Semiconductors, VLSI, Electronics, Digital Systems AI, USA
- Jeferson Nobre Federal University of Rio Grande do Sul, Brazil
- Éric Renault ESIEE Paris – Univ. Gustave Eiffel, France
- Henry Yu Huawei, Canada