Check the GIIS2026 edition at giis2026.giis-conference.org

Tutorials

Feb. 25, 2025

Tutorial-1: Toward Secure and Sustainable O-RAN networks

Rami Langar (Ecole de Technologie Supérieure, ÉTS-Montréal (Canada) and University Gustave Eiffel (France))

ABSTRACT:

The next-generation radio access network (RAN), open RAN (O-RAN), has been introduced as an industry-standard framework that supports interoperability between equipment from different vendors and offers flexibility, including efficient network slicing with various functional split options for 5G and beyond mobile networks. However, two important questions must be addressed to ensure the widespread deployment of O-RAN in 5G and beyond: how to improve mechanisms for detecting cyberattacks and how to meet quality-of-service (QoS) requirements, while considering energy consumption when placing network functions within the RAN. In this talk, we will provide insights into how these two research challenges are being addressed from both algorithmic and practical perspectives and present our recent results toward building more secure and sustainable O-RAN networks.

PRESENTER'S BIO:

Rami Langar is a Full Professor of Computer Science affiliated with École de Technologie Supérieure (ÉTS), Montréal, Canada, since June 2021, and University Gustave Eiffel, Paris, France since September 2016. He was an Associate Professor at LIP6, Sorbonne University (former University Pierre and Marie Curie), Paris, France between 2008 and 2016. He received the M.Sc. degree in network and computer science from Sorbonne University in 2002; and the Ph.D. degree in network and computer science from Telecom ParisTech, Paris, France, in 2006. In 2007 and 2008, he was with the School of Computer Science, University of Waterloo, ON, Canada, as a Post-Doctoral Research Fellow. His research interests include resource management in 5G/6G and O-RAN networks, green network slicing, mobile edge cloud offloading, AI/ML-based network slice security, and Network Digital Twin.

Feb. 26, 2025

Tutorial-2: Graph Neural Networks for Network Slicing: Promises, Challenges, and Future Directions

Yassine Hadjadj-Aoul (Full professor, University of Rennes (France))

ABSTRACT:

Due to their dynamic nature and the multitude of involved parameters, network optimization problems are typically complex. The complexity of these problems is further increased by the distributed nature of these networks, coupled with the need to simultaneously take into account the variety of objectives and constraints, mainly related to the supported services. Conventional optimization methods generally fail to address these multiobjective problems, as they fail to provide scalable and robust solutions capable of dynamically adapting to changing network conditions. To overcome these obstacles, several machine learning-based approaches, and particularly reinforcement learning, have emerged in recent years. Although effective, these approaches are generally unable to grasp the graph topology of the networks and the richness of information, they also pain to generalize the learning, in addition to being unexplainable black boxes, which limits the practical utility of these approaches. In this context, Graph Neural Networks (GNNs) have emerged as a promising approach, leveraging the power of deep learning to process graph-structured data effectively, which is typically needed in several networking problems.

This tutorial will explore the applications of GNNs in network optimization problems such as virtual services’ placement for network slicing. We will discuss the ability of GNNs to capture graph structures and apprehend representations directly from network data to enable more efficient and intelligent resource allocation strategies. By exploring both the promises and limitations of GNNs, this talk aims to provide a comprehensive understanding of their applicability in network management, and opens the door for future research directions in this rapidly evolving field.

PRESENTER'S BIO:

Yassine HADJADJ AOUL (yhadjadj <<AT>> irisa.fr) is a Full Professor at the University of Rennes, France, since 2022. He is a member of the IRISA Laboratory and the INRIA Ermine team-project. He earned a B.Sc. in Computer Engineering with high honors from Mohamed Boudiaf University, Oran, Algeria, in 1999, and a Ph.D. in Computer Science from the University of Versailles in 2007. Following his Ph.D., Dr. Hadjadj expanded his research experience as a Postdoctoral Researcher at the University of Lille 1 and as a Marie Curie Research Fellow under the EU FP6 EIF program at the National University of Ireland, Dublin (UCD). He later joined the University of Rennes as an Associate Professor before attaining his current position.

His primary research interests include congestion control, mobile cloud networking, network functions virtualization (NFV), and QoS/QoE provisioning.

Feb. 27, 2025

Tutorial-3: Design, Analysis, and Optimization of Sustainable Communication Networks: Achieving Energy Efficiency and EMF Safety

Ahmed Elzanaty (University of Surrey, United Kingdom)

Mustafa A. Kishk (Maynooth University, Ireland)

Mohamed-Slim Alouini (KAUST, Saudi Arabia)

ABSTRACT:

This tutorial focuses on the design, performance analysis, and optimization of sustainable communication networks, integrating energy efficiency and electromagnetic field (EMF) exposure management as essential features. Participants will examine techniques for improving the energy efficiency of Integrated Access and Backhaul (IAB) networks and analyze the performance of aerial networks employing UAVs for optimized resource allocation and communication reliability.

The session includes the evaluation of RF-powered IoT systems in rural areas and explores approaches to enhance uplink transmission to Low Earth Orbit (LEO) satellites. Addition- ally, it addresses the analysis of EMF exposure in large- scale networks, discusses challenges associated with network densification, and explores mitigation strategies, including the use of Reconfigurable Intelligent Surfaces (RISs) in mmWave communications. Health considerations related to 5G networks are also assessed, providing a balanced approach to designing sustainable communication systems.

This tutorial equips researchers and professionals with practical insights and methodologies for creating networks that meet the demands of energy efficiency, performance, and safety in a sustainable manner.

Keywords:

Sustainable Networks, Design, Performance Analysis, Energy Efficiency, IAB Networks, UAV, RF- Powered IoT, LEO Satellites, EMF Exposure, RIS, 5G Health.

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