IEEE/IFIP Network Operations and Management Symposium
6–10 May 2024 // Seoul, South Korea

IPSN 2024

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3rd International Workshop on Intelligence Provisioning for Network and Service Management in Softwarized Networks (IPSN) in conjunction with IEEE/IFIP NOMS 2024

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Thanks to the rapid growth in network bandwidth and connectivity, networks and distributed systems have become critical infrastructures that underpin much of today’s Internet services. However, networks are highly complex, dynamic and time-varying systems, such that the statistical properties of networks and network traffic cannot be easily modeled. Moreover, the trend towards highly integrated networks with diverse underlying access technologies to support simultaneously multiple vertical industries has demanded complex operations in network management. With the advent of Artificial Intelligence (AI) and Machine Learning (ML) techniques, along with the flexibility and programmability provided by the so-called softwarized networks and its enablers, Software-Defined Networks (SDN) and Network Function Virtualization (NFV), challenges associated to the complex network management operation of forthcoming networks can be tackled by exploiting the combination of AI/ML techniques and softwarized networks.

The main goal of IPSN Workshop is to present state-of-the-art research results and experience reports in the area of AI/ML for network management on softwarized networks, addressing topics such as artificial intelligence techniques and models for network and service management in softwarized networks; smart service orchestration, training process at the constrained edge, dynamic Service Function Chaining, Intent and policy based management, centralized vs distributed control of SDN/NFV based networks, analytics and big data approaches, knowledge creation and decision making. This workshop offers a timely venue for researchers and industry partners to present and discuss their latest results in the application of network intelligence to the management of softwarized networks. Topics of interest include, but are not limited to:

- Data-driven management of software defined networks
- Deep and Reinforcement learning for networking and communications
- Experiences and best-practices using AI/ML in operational networks
- Fault-tolerant network protocols exploiting AI/ML methods
- Implications and challenges brought by computer networks to machine learning theory and algorithms
- Innovative architectures and infrastructures for intelligent networks
- Intelligent energy-aware/green softwarized networks
- Intent & Policy-based management for intelligent networks
- Methodologies for network problem diagnosis, anomaly detection and prediction
- Network Security based on AI/ML techniques in softwarized networks
- Open-source networking optimization tools for AI/ML applications
- Protocol design and optimization using AI/ML in softwarized networks
- Reliability, robustness and safety based on AI/ML techniques
- Routing optimization based on flow prediction in softwarized networks
- Self-learning and adaptive networking protocols and algorithms for softwarized networks
- AI/ML for network management and orchestration in softwarized networks
- AI/ML for network slicing optimization in softwarized networks
- AI/ML for service placement and dynamic Service Function Chaining in softwarized networks
- AI/ML for C-RAN resource management and medium access control
- AI/ML for multimedia networking in softwarized networks
- AI/ML support for ultra-low latency applications in softwarized networks


Authors are invited  to submit original contributions through . Submitted manuscripts should use IEEE 2-column conference style and are limited to 6 pages (including references). Short/Work in progress papers are also welcome (4 page limit, including references). For more details, please check


Paper Submission Deadline: 2 Feb. 2024 (Extended)
Paper Acceptance Notification: 1 March 2024
Camera-ready Version Due: 15 March 2024

Best papers will be invited to extend their work to a Journal Special Issue. To be confirmed.

** Program **

Date: May, 10th, 2024
Room: Bipa

9:00 – 9:15 IPSN Presentation Jaime Galán-Jiménez and Marco Polverini
9:15 – 10:30 Keynote1:
AI/ML for Networking in the Era of Programmable Data Planes: Are We There Yet?
Luciano Paschoal Gaspary (Federal University of Rio Grande do Sul, Brazil)
10:30 – 11:00 Coffee Break
11:00 – 12:30 perfSONAR: Enhancing Data Collection through Adaptive Sampling Ali Mazloum (University of South Carolina, USA), Ali AlSabeh (University of South Carolina, USA), Elie Kfoury (University of South Carolina, USA), Jorge Crichigno (University of South Carolina, USA)
Proposal and Investigation of a Distributed Learning Strategy for training of Neural Networks in Earth Observation Application Scenarios Francesco Valente (University of Rome “Sapienza”, Italy), Francesco Giacinto Lavacca (University of Rome “Sapienza”, Italy), Tiziana Fiori (University of Rome “Sapienza”, Italy), Vincenzo Eramo (University of Rome “Sapienza”, Italy)
Adaptive Configuration with Deep Reinforcement Learning in Software-Defined Time-Sensitive Networking Mengjie Guo (Beijing University of Posts and Telecommunications, People’s Republic of China), Guochu Shou (Beijing University of Posts and Telecommunications, People’s Republic of China), Yaqiong Liu (Beijing University of Posts and Telecommunications, People’s Republic of China), Yihong Hu (Beijing University of Posts and Telecommunications, People’s Republic of China)
12:30 – 14:00 Lunch Time
14:00 – 15:30 Keynote2:
Towards Efficient Network and Service Management across the Cloud Continuum
José Santos (Ghent University – imec, IDLab, Belgium)
Inferring Visibility of Internet Traffic Matrices Using eXplainable AI Cristian Zilli (Politecnico di Torino, Italy), Alessio Sacco (Politecnico di Torino, Italy), Doriana Monaco (Politecnico di Torino, Italy), Okwudilichukwu Okafor (Saint Louis University, USA), Flavio Esposito (Saint Louis University, USA), Guido Marchetto (Politecnico di Torino, Italy)
15:30 – 16:00 Coffee Break
16:00 – 17:00 Improving the Traffic Engineering of SDN networks by using Local Multi-Agent Deep Reinforcement Learning José Gómez-delaHiz (University of Extremadura, Spain), Jaime Galán-Jiménez (University of Extremadura, Spain)
Multi-armed Bandits for Self-distributing Stateful Services across Networking Infrastructures Frederico Meletti Rappa (Instituto de Computação da Universidade Estadual de Campinas, Brazil), Roberto Rodrigues-Filho (UFSC, Brazil), Alison R. Panisson (PUCRS, Brazil), Leandro Marcolino (Lancaster University, United Kingdom), Luiz Fernando Bittencourt (UNICAMP, Brazil)
17:00 – 17:25 Panel Jorge Crichigno (University of South Carolina, USA), José Santos (Ghent University – imec, IDLab, Belgium), Francesco Giacinto Lavacca (University of Rome “Sapienza”, Italy)
17:25 – 17:30 Best Paper Award and Closing Jaime Galán-Jiménez and Marco Polverini