2025Activity reportProject-TeamAGORA
RNSR: 201722227R- Research center Inria Lyon Centre
- In partnership with:Institut national des sciences appliquées de Lyon
- Team name: Wireless Networks for Digital Cities
- In collaboration with:Centre d'innovation en télécommunications et intégration de services
Creation of the Project-Team: 2018 April 01
Each year, Inria research teams publish an Activity Report presenting their work and results over the reporting period. These reports follow a common structure, with some optional sections depending on the specific team. They typically begin by outlining the overall objectives and research programme, including the main research themes, goals, and methodological approaches. They also describe the application domains targeted by the team, highlighting the scientific or societal contexts in which their work is situated.
The reports then present the highlights of the year, covering major scientific achievements, software developments, or teaching contributions. When relevant, they include sections on software, platforms, and open data, detailing the tools developed and how they are shared. A substantial part is dedicated to new results, where scientific contributions are described in detail, often with subsections specifying participants and associated keywords.
Finally, the Activity Report addresses funding, contracts, partnerships, and collaborations at various levels, from industrial agreements to international cooperations. It also covers dissemination and teaching activities, such as participation in scientific events, outreach, and supervision. The document concludes with a presentation of scientific production, including major publications and those produced during the year.
Keywords
Computer Science and Digital Science
- A1.2.1. Dynamic reconfiguration
- A1.2.3. Routing
- A1.2.4. QoS, performance evaluation
- A1.2.6. Sensor networks
- A1.2.8. Network security
- A1.3.6. Fog, Edge
- A1.5.2. Communicating systems
- A1.6. Green Computing
- A3.3.3. Big data analysis
- A5.10.3. Planning
- A5.10.6. Swarm robotics
- A7.1. Algorithms
- A8.2. Optimization
- A9.2.1. Supervised learning
- A9.2.2. Unsupervised learning
- A9.2.3. Reinforcement learning
Other Research Topics and Application Domains
- B3.4.1. Natural risks
- B3.4.3. Pollution
- B6.2.2. wireless networks
- B6.2.3. Satellite networks
- B6.2.5. Non Terrestrial Networks
- B6.2.6. Cellular networks (3G,… 6G)
- B6.3.2. Network protocols
- B6.3.3. Network Management
- B6.4. Internet of things
- B7.2. Smart travel
- B8.1.2. Sensor networks for smart buildings
- B8.2. Connected city
1 Team members, visitors, external collaborators
Research Scientists
- Ahmed Boubrima [INRIA, ISFP]
- Juan A. Fraire [INRIA, ISFP, HDR]
- Catherine Rosenberg [INRIA, Chair, from Oct 2025]
Faculty Members
- Hervé Rivano [Team leader, INSA LYON, Professor, HDR]
- Walid Bechkit [INSA LYON, Associate Professor, until Aug 2025, HDR]
- Kamal Benzekki [INSA LYON, Certified Teacher, from Oct 2025]
- Oana Iova [INSA LYON, Associate Professor]
- Razvan Stanica [INSA LYON, Associate Professor, HDR]
- Fabrice Valois [INSA LYON, Professor, HDR]
Post-Doctoral Fellows
- Evelyne Akopyan [INRIA, Post-Doctoral Fellow, until Aug 2025]
- Hannaneh Barahouei Pasandi [INRIA, Post-Doctoral Fellow, until Jul 2025]
- Jana Koteich [INSA LYON, Post-Doctoral Fellow]
- Sachit Mishra [INRIA, from Aug 2025]
- Nina Tamdrari [INRIA, Post-Doctoral Fellow]
- Simon Weinberger [INRIA, Post-Doctoral Fellow, from Dec 2025]
- Zhiyi Zhang [INRIA, Post-Doctoral Fellow, from Mar 2025 until Aug 2025]
PhD Students
- Mohamed Sami Assenine [INSA Lyon]
- Youssef Badra [INRIA, INSAVALOR]
- Guillermo Benito Calvino [INRIA]
- Anais Boumendil [INSA LYON]
- Alexander Ylnner Choquenaira Florez [INRIA]
- Benoit Coeugnet [Kineis, CIFRE, from Oct 2025]
- Geymerson Dos Santos Ramos [INRIA]
- Carlos Fernandez Hernandez [INSA LYON]
- Diego Maldonado Munoz [INSA LYON]
- Audrey Nageotte [SPIE, CIFRE]
- Sekinat Yahya [INSA LYON, until Jul 2025]
- Shengcong Zhang [INSA LYON, from Nov 2025]
- Zhiyi Zhang [INSA LYON, until Jan 2025]
Technical Staff
- Abdellatif Bendjeddou [INRIA, Engineer, from Dec 2025]
- Nicolas Valle [INRIA, Engineer]
Interns and Apprentices
- Abdellatif Bendjeddou [INSA Lyon, Intern, until Jul 2025]
- Benoit Coeugnet [INRIA, Intern, until Jun 2025]
- Noe Fregonese [INRIA, Intern, from Jul 2025]
- Nahuel Gomez Raguileo [INRIA, Intern, until Apr 2025]
- Longrui Ma [INRIA, Intern, from Apr 2025 until Oct 2025]
- Lucas Poulhe [INRIA, Intern, from May 2025 until Aug 2025]
- Lisa Scappaticci [INRIA, Intern, from May 2025 until Jul 2025]
Administrative Assistants
- Lauretta Lauret [INRIA, from Jun 2025]
- Wassil Moulin [INSA Lyon, until Aug 2025]
- Noémie Rodrigues [INRIA, until May 2025]
External Collaborator
- Walid Bechkit [UNIV LYON II, from Sep 2025, HDR]
2 Overall objectives
The main focus of the Agora team is on the specific challenges when considering wireless network architectures dedicated to urban environments, including connected and smart cities. The smart city represents a constantly reshaped concept, embracing the future of dense metropolitan areas. It refers to efficient and sustainable infrastructure, improving citizens' quality of life, and protecting the environment. However, a consensus on the Smart City philosophy is that it will be primarily achieved by leveraging a clever integration of Information and Communication Technologies (ICT) in the urban tissue.
Indeed, ICTs enable an evolution from the current duality between the physical world and its digitized counterpart to a continuum in which digital content and applications seamlessly interact with classical infrastructures and services. Smart Cities are often described by their digital services, which are inherently dependent on dense measurements of the city environment and activities, the collection of this data, its processing into information, and its redistribution. Therefore, the networking infrastructure is critical in enabling advanced services, particularly the wireless infrastructure that supports high user density and mobility.
From a wireless networking viewpoint, the digitization of cities can be seen as a paradigm shift extending the Internet of Things (IoT) to a citizen-centric model to leverage the massive data collected by pervasive sensors, connected mobile or fixed devices, and social applications. We aim to capture these aspects and design network architectures and protocols that are relevant to them.
In addition to our focus on ICTs in urban areas, we also work on their extension to any scenario where coverage challenges meet high density, such as satellite-IoT constellations or networks for rural and geographically isolated areas.
While our work is grounded on the properties of the wireless technologies we study, including a significant experimental dimension, our ambition is to address more general scientific challenges of network architectures. We can cluster these architectures into three main kinds:
- Carefully deployed topologies such as cellular networks and environmental monitoring,
- Planned and dynamic topologies such as a fleet of drones and satellite communications,
- Uncontrolled topologies, such as individual IoT and self-deployable networks.
The team aims to contribute to the following consequent challenges of data collection wireless networks in smart environments:
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Wireless network deployment
Multi-technology, multi-paradigm networks foster the need for federated network architectures that integrate both asynchronous and synchronous communication domains. The challenge is to understand how to orchestrate this diversity, while defining the networking metrics adequately in the perspective of evolving and intermittent topologies.
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Wireless protocols design
The multi-technology, multi-architecture approach at the heart of the convergence between cellular and NTN architectures will intensely focus on protocols for asset tracking, two-sided mobility management, and network function positioning and configurations. We aim to bridge our research on airborne, satellite, and virtualized cellular networks.
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Network data analysis
The analysis of network data or metadata generated by cellular infrastructure, mobile hotspots, or core networks is leveraged to design algorithms for understanding spatiotemporal aspects of mobility and wireless coverage, provisioning edge computing resources in an urban-scale infrastructure, or performing anomaly detection.
3 Research program
The Agora research program is organized in three axes, which are addressed in the team following the same general methodology that aims at combining:
- Modeling to get insights on average and asymptotic behaviors,
- Simulation to investigate large-scale networks and average behavior,
- Experimentation to get validation from real devices and users.
Modeling is typically mathematical optimization, stochastic performance evaluation, or Machine Learning algorithms. Discrete event simulations mainly focus on networks, environments, or user mobility. Experiments can be conducted on proof-of-concept prototypes, lab-controlled test beds, or real-world deployments and data collection.
3.1 Wireless network deployment
The team addresses challenges in the three following directions:
- We develop optimization models and heuristics for network component deployment, with a specific focus on wireless sensor networks (for monitoring environmental phenomena) and direct-to-satellite communications (to improve IoT coverage, especially for outside areas).
- We investigate the impact of network function deployment enabled by their virtualization on the performances of radio access networks and self-deployable cellular networks.
- We develop and experiment self-configuration and self-healing protocols to enable deployments without human in the loop.
3.2 Wireless protocols design
In this axis, we investigate design challenges of network mechanisms and protocols such as medium access, medium sharing, and routing protocols.
- Such mechanisms are addressed with a focus on enabling self-organization, self-healing and opportunistic communications.
- New technologies such as low power and long range networks, non terrestrial networks, and human-centric networks yield intermittent connectivity and dynamic architectures. We investigate them in terms of performance, scalability, sustainability, etc.
- We combine our expertise in these diverse architectures and consider hybrid networks, that we foresee as the relevant solution for supporting dense and dynamic topologies.
3.3 Network data analysis
In this axis, we focus on the spatio-temporal characteristics of the network usage and data collected in the three following directions.
- Mobile data are analyzed to understand the coupling between users activity and the network usage.
- Data aggregation is investigated with the objective to have the most efficient and sober usage of wireless communications.
- Finally distributed sensor calibration will exploit the wireless network to increase the reliability of the collected data and ultimately improve the cost/quality trade-off of a wireless sensor network.
4 Application domains
4.1 Smart Cities
One major characteristic of modern societies is that they are prevalently urban. Consequently, the contributions of the Agora team are in particular applied to provide solutions tailored to the emergence of the Internet of Things (IoT) and to Smart Cities applications. A major motivation of the team is the forthcoming explosion of the number of connected devices and the numerous wireless network technologies, supporting potential end device mobility. In particular, low cost - small data devices are supposed to be densely deployed in our environment, fostering the interest for a convergence of the traditional wireless networking paradigms.
Smart City is a constantly reshaped concept, embracing the future of dense metropolitan areas, with references to efficient and sustainable infrastructure, improving citizens’ quality of life and protecting the environment. A consensus on the Smart City philosophy is however that it will be primarily achieved by leveraging a clever integration of ICT in the urban tissue. Indeed, ICTs are enabling an evolution from the current duality between the real world and its digitized counterpart to a continuum in which digital contents and applications are seamlessly interacting with classical infrastructures and services. Smart Cities are often described by the digital services that should be provided which are inherently dependent on dense measurements of the city environment and activities, the collection of these data, their processing into information, and their redistribution. The networking infrastructure plays therefore a critical role in enabling advanced services, in particular the wireless infrastructure supporting density and mobility. In such wireless network infrastructure, whether it is a cellular one or an IoT one, new features arise: mobile devices to provide connectivity (e.g. UAVs), on-demand deployment, heterogeneous technologies, that shape the future of wireless networks.
From a wireless networking viewpoint, the digitization of cities can be seen as a paradigm shift extending the IoT to a citizen-centric model in order to leverage the massive data collected by pervasive sensors, connected mobiles or fixed devices, and social applications.
5 Social and environmental responsibility
5.1 Impact of research results
Some of our research activities are specifically focused on social and environmental responsibility:
- We have a long line of collaborations with local authorities (Lyon Metropolis and the city of Lyon, city of Villeurbanne) and non-governmental organizations (Atmo-AuRA) on environmental issues such as air quality and urban warming. Indeed, since the preliminary project UrpolSens (Wireless SENSor Networks for URban POLlution Monitoring) funded in 2015 by the Labex IMU, the Agora Inria team is building a long success story about air and pollution monitoring. With several research projects and bilateral collaborations with companies (e.g., Total), we leverage an interdisciplinary approach to efficiently monitor chronic and accidental pollution as well as Urban Heat Island (UHI).
- Furthermore, we have developed at the Agora team a culture of collaborating with researchers in social and human sciences. This has been intiated within the LabEx IMU and the Ecole Urbaine de Lyon, and had been sustained in academic chairs and with industrial partners. Following this direction, and while collaborating with geographers, geomaticians and anthropologists, we have measured and studied the cyclist behavior and the cyclability of the urban environment. Our work on cyclist activity is trying to build a contribution to the necessary transition to decarbonized mobilities. In our recent efforts, we proposed deep reinforcement learning (DRL) solutions to optimize traffic light phases in order to increase the safety of cyclists. This is the first step toward replicating classic networking mechanisms (e.g., virtualization and adaptative scheduling) into dynamic urban infrastructures.
- Energy has always been an important metric in wireless networking research. More recently, we have started to investigate the energetic consumption of cellular networks in more details. A significant mechanism in reaching network flexibility is network slicing, but this introduces new challenges in the development of sustainable network operations. Guaranteeing slice requirements comes at the cost of additional energy consumption. To this end, we have been studing the problem of deploying network slices to minimize energy consumption and maximize the user quality of service (QoS).
- Moreover, since the introduction of the paradigm of self-deployable cellular networks, we have been investigating the evolution of the cellular network architecture and the impact of such networks on the control plane's protocols. In this regard, we are contributing to several aspects such as: network function placements, the user association procedure, mobility management, etc. We show that self-deployable cellular networks can be used for first responders when the telecommunication infrastructure is totally, or partially, damaged. Self-deployable cellular networks are a key enabler technology for humanitarian engineering to allow a fast and efficient deployment of a telecommunication infrastructure for NGOs.
- Finally, we are working on frugal AI in order to address the critical need for sustainability when training deep learning. The outcome of our research will allow us to achieve high energy gains with minimal accuracy loss. Our vision is that when AI is applied in embedded systems, it should be done while minimizing the pollution emissions associated with this technology.
6 Highlights of the year
6.1 Awards
- Walid Bechkit, Oana Iova, Hervé Rivano, Razvan Stanica, and Fabrice Valois hold the RIPEC award.
- Oana Iova received the Scientific Distinction of INSA Lyon for the research work in the field of computer networks and distributed systems.
- Catherine Rosenberg has been awarded an « Inria International Chair » in the AGORA team for the 2025-2030 period.
- Fabrice Valois has been promoted to Professeur Classe Exceptionnelle, INSA Lyon, since September 2025.
- The paper 1 was runner-up for the best paper award at WoWMoM 2025, the 26th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks.
- The paper 27 was also runner-up for the best paper award at ASMS/SPSC 2025, the 12th Advanced Satellite Multimedia Systems Conference and the 18th Signal Processing for Space Communications Workshop.
6.2 HDR and PhD defences
- Juan A. Fraire defended his HDR in May, 2025.
- Zhiyi Zhang defended his PhD in January, 2025.
- Sekinat Yahya defended her PhD in July, 2025.
6.3 Other highlights
- Walid Bechkit was appointed Full Professor at Université Lyon 2 in September 2025, after successfully passing the professor examination. He has maintained his involvement with the AGORA team as an external collaborator since then.
- Razvan Stanica has been promoted to Full Professor at INSA Lyon (effective beginning 2026).
- Evelyne Akopyan joined INSA Toulouse as Associate Professor (MdC) in September, 2025.
- Zhiyi Zhang joined Paris-Saclay University (UVSQ Campus) as Associate Professor (MdC) in September, 2025.
7 Latest software developments, platforms, open data
7.1 Latest software developments
7.1.1 Dense LoRaSim
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Name:
Extension to support dense LPWAN in LoRaSim
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Keyword:
LoRaWAN
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Functional Description:
In the settings of our dense networks research topic, we have modified the LoRaSim simulator so that it supports up to a million devices, while keeping a realistic modelisation of the channel. This will allow us to evaluate the scalability of different algorithms and protocols in a realistic scenario. We also created a fork to support ultra dense network emulation.
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Contact:
Fabrice Valois
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Participants:
Oana Iova, Hervé Rivano, Fabrice Valois
7.1.2 ELoRa
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Name:
Extension of ELoRa to support the open source implementation of The Thing Stack
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Keywords:
LoRaWAN, Downlink scheduling, The Thing Stack
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Functional Description:
The ELoRa network simulator integrates the ns-3 simulator with the known CS network server. To recognize LoRaWAN packets and to manage the simulated LoRaWAN network, end devices must be registered on the network server. ELoRa uses libcurl to communicate with the REST API from the network server, and implements the Activation by Personalization (ABP) to register and activate end devices. We extended the ELoRa simulator to support the open source implementation of The Thing Stack maintained by The Things Industries. The main changes are related to the registration of end devices, as the commands to communicate with the REST API are different, as well as the parameters to be configured. Unlike the CS, the component that communicates with gateways is the Gateway Server. This structure also implements the UDP Packet Forwarder to forward and receive the DL and UL packets to and from the gateway, respectively. Moreover, the Gateway Server implements more operations than the CS Gateway Bridge, such as monitoring the time on air, the duty cycle and the dwell time.
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Contact:
Oana Iova
7.1.3 FLoRaSat
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Name:
Extension of FLoRa for Direct-to-Satellite IoT
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Keywords:
Iot, Satellite, LoRaWAN
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Functional Description:
Direct to Satellite IoT (DtS-IoT) is a promising approach to deliver data transfer services to IoT devices in remote areas where deploying terrestrial infrastructure is not appealing or feasible. In this context, low-Earth orbit (LEO) satellites can serve as passing-by IoT gateways to which devices can offload buffered data to. However, transmission distances and channel dynamics, combined with highly constrained devices on the ground makes DtS-IoT a very challenging problem. To explore DtS-IoT, we propose to extend the Flora simulator based on Omnet++: i) to support Class B end-devices ii) to support LEO orbits iii) to support large scale satellite constellation. It allows us to model and simulate realistic DtS-IoT scenarios to measure the expected performance of LoRaWAN in a satellite context. Available on: https://gitlab.inria.fr/jfraire/florasat
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Contact:
Juan Andres Fraire
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Participants:
Alexander Ylnner Choquenaira Florez, Benoit Coeugnet, Juan Andres Fraire, Oana Iova, Fabrice Valois
7.1.4 UTOPIA-S
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Name:
aUTonomous OPtimised aIr quAlity - Software
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Keywords:
Air Quality, Sensors
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Functional Description:
Since 2015 we develop optimized, efficient and autonomous solutions for physical phenomenons monitoring. We focus on pollutants (large band of gasses and particles) and urban heat islands, but our solutions are very generic and can be adapted with ease to monitor other phenomenons.
UTOPIA-S is an embedded software written in Arduino destined to run in a generic sensor architecture (UTOPIA-H) we developed for our global solution. UTOPIA-S allows an optimized, reliable and customizable use of the UTOPIA-H based sensor nodes.
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Release Contributions:
- Very low power consumption - Distant reconfiguration of LoRa parameters - Added support for other sensors - Improved stability - Data saving in a SD card - LoRa parameters saving in the EEPROM
- Publication:
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Contact:
Walid Bechkit
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Participants:
Walid Bechkit, Ahmed Boubrima, Hervé Rivano
7.1.5 SD-MANET
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Name:
Service Discovery for Mobile Ad-hoc Networks
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Keywords:
Protocoles, La simulation
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Functional Description:
SD-MANET is a simulator to benchmark service discovery protocols in heterogeneous networks. You can define complex topologies and dynamic scenarios, with fine-grained services. It is based on OMNeT++, is fully portable and automated from experiment campaign configuration to data analysis.
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Contact:
Fabrice Valois
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Participants:
Hervé Rivano, Razvan Stanica, Nina Tamdrari, Fabrice Valois
7.1.6 IPN-V
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Name:
The Interplanetary Network Visualizer
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Keyword:
Visualization
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Functional Description:
Leveraging the power of Unity 3D and C#, IPN-V provides a user-friendly 3D interface for the interactive visualization of interplanetary networks, incorporating contact tracing models to represent line-of-sight communication constraints accurately. IPN-V supports importing and exporting contact plans compatible with established space communication standards, including NASA’s ION and HDTN formats.
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Contact:
Juan Andres Fraire
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Participants:
Alice Le Bihan, Juan Andres Fraire
7.2 New platforms
Participants: Walid Bechkit, Ahmed Boubrima, Oana Iova, Hervé Rivano, Fabrice Valois.
7.2.1 PPAIR Plateforme LoRa - Campus Connecté
The project aims at providing a platform that offers connectivity through a long-range, low-energy network to smart objects. The platform uses LoRa technology, which offers a wide connectivity, covering the entire INSA Lyon campus and providing a data collection service to all campus users. The main purpose of the LoRaWAN platform is: i) research (researchers can use it for studying reliability and capacity problems, privacy related challenges, etc.), and ii) teaching (several courses from INSA, especially in the Telecom department can use this platform as a pedagogical tool). Since 2019, this platform is used in the European Project Interreg Med ESMARTCITY and for the PHC Ulysses (joint collaboration with Nimbus Center, Ireland).
7.2.2 UrPolSens / UTOPIA-H platforms
We designed an energy-efficient air pollution monitoring platform from scratch. A microcontroller is integrated into a custom-designed printed circuit board. Using a high-precision ADC, a micro-SD card reader, and a LoRaWAN communication module, it drives several environmental probes, stores the measurements, and transmitting them to gateways. These can be connected to our servers through a 4G connection. The platform has been optimized to operate autonomously on solar energy over extended periods and refined for reliability. This platform meets industrial requirements, as part of our collaboration with the TotalEnergies LQA lab. It has been used in two operational deployments: the first on an onshore industrial site to assess pollutant emissions, and the second on an offshore site for monitoring occupational exposure to pollutants.
7.3 Open data
In 2025, we published the Netmob 2025 dataset 3, a unique dataset from a GNSS-based mobility survey conducted in the Ile-de-France region. Volunteers were equipped with a GNSS receiver that determines position and velocity using signals from global navigation satellite systems. The result is a high-resolution dataset that captures the mobility behavior of over 3,300 volunteers between October 2022 and May 2023. All participants provided informed consent for the data collection, which was conducted in accordance with data protection regulations. They carried the tracking device for seven consecutive days and maintained digital (or optional paper) travel diaries. All collected information was anonymized and validated through follow-up phone interviews to ensure accuracy while minimizing intrusiveness.
Furthermore, since 2019, we have been continuously collecting a dataset of LoRa activity on the campus through our experimental platform. The dataset is not yet consolidated, mainly because of a lack of resources, but this will be the case in a short time. This dataset will be hopefully openly disseminated in 2025/2026. We assume it will be helpful for a wide public of researchers.
8 New results
8.1 Wireless network deployment
Participants: Ahmed Boubrima, Juan A. Fraire, Hervé Rivano, Razvan Stanica.
ICE-CREAM: Multi-agent Fully Cooperative Decentralized Framework for Energy Efficiency in RAN Slicing
Network slicing is one of the major catalysts proposed to turn future telecommunication networks into versatile service platforms. Building sustainable mobile networks, with the least amount of resources used, is crucial today, for both economic and environmental reasons. As a result, mobile operators need to find a middle ground between these two objectives – a tough nut considering they are both antithetical and important. In this light, we investigate in 10 a joint slice activation/deactivation and user association problem, with the aim of minimizing energy consumption and maximizing the QoS. The proposed multI-agent fully CooperativE deCentRalizEd frAMework (ICE-CREAM) addresses the formulated joint problem, with agents acting at two different granularity levels. We evaluate ICE-CREAM using a real-world dataset that captures the spatio-temporal consumption of three different mobile services in France. Experimental results demonstrate that the proposed solution provides more than 30% energy efficiency improvement compared to a configuration where all the slice instances are always active while maintaining the same level of QoS.
Joint Contact Planning for Navigation and Communication in GNSS–Libration Point Systems
Integrating LP satellites with GNSS into a joint constellation enables a more robust and comprehensive Positioning, Navigation, and Timing (PNT) system, while also extending navigation and communication services to spacecraft operating in cislunar space (i.e., users). However, the long propagation delays between LP satellites, users, and GNSS satellites result in significantly different link durations compared to those within the GNSS constellation. Scheduling inter-satellite links (ISLs) is a core task of Contact Plan Design (CPD). Existing CPD approaches focus exclusively on GNSS constellations, assuming uniform link durations, and thus cannot accommodate the heterogeneous link timescales present in a joint GNSS-LP system. To overcome this limitation, we introduce in 20 a Joint CPD (J-CPD) scheme tailored to handle ISLs with differing duration units across integrated constellations. The key contributions of J-CPD are: (i):introduction of LongSlots (Earth-Moon scale links) and ShortSlots (GNSS-scale links); (ii):a hierarchical and crossed CPD process for scheduling LongSlots and ShortSlots ISLs; (iii):an energy-driven link scheduling algorithm adapted to the CPD process. To our knowledge, this is the first CPD framework to jointly optimize navigation and communication in GNSS-LP systems, representing a key step toward unified and resilient deep-space PNT architectures.
Quantifying Edge Server Placement in LEO Constellations: A Comparative Emulation of Space and Terrestrial Cloud
Smart strategic placement of Multi-access Edge Computing (MEC) resources in space or on Earth could play a critical role in meeting these performance demands. Our work in 12 introduces a comprehensive analysis of Round-Trip Time (RTT) for computation services under various edge server placement strategies, including space, terrestrial, and hybrid cloud configurations. We use MeteorNet, a novel real-time emulation platform that integrates orbital propagation models and networking virtualization, to evaluate realistic satellite constellations and flightgrade application behavior at system-level scale. Our formulation of the edge server placement problem as a non-linear integer program enables quantifiable comparison of configurations, subject to constraints imposed by dynamic topologies and infrastructure limits. Through experimentation, we identify conditions under which terrestrial edge clouds provide optimal latency and cases where space-based architectures outperform their ground-based or even hybrid counterparts. We also demonstrate how server placement strategies, such as cross-plane, along-orbit, and farthest-point sampling, affect latency performance, as reflected in the average routing path length within the constellation.
Network Size Estimation in DtS-IoT: A LoRaWAN Approach for Satellite Constellations
Low Earth Orbit (LEO) constellations are pivotal for the global connectivity of Internet of Things (IoT) networks. Although LoRa-based solutions provide low-cost connectivity to constrained devices in DtS-IoT networks, scalability remains a significant challenge due to heavy channel congestion associated with large-scale deployments. The LoRa Optimistic Collision Information-based (L-OCI) mechanism has been designed to estimate efficiently the network size of a LoRa-based DtS-IoT deployment. It enables a passing satellite to gauge the potential congestion in the served region by estimating the number of active ground nodes within its coverage area. However, this mechanism was devised to operate assuming a single LEO satellite. Our work in 31 introduces the constellation LOCI (CL-OCI), a new methodology for network size estimation designed for LEO satellite constellations. We thoroughly tested CL-OCI using FLoRaSat, a discrete-event satellite constellation simulator with realistic orbital DtS-IoT scenarios. Results indicate a substantial improvement in scalability, doubling the maximum number of nodes CL-OCI can estimate, and a sevenfold reduction in energy wasted due to collided transmissions compared to the baseline single-satellite L-OCI.
Toward Energy Efficiency and Fairness in UAV-Based Task Offloading
In this work 16, we propose a system where Unmanned Aerial Vehicles (UAVs) serve as mobile relays between UEs and MEC servers. This results in a joint optimization framework combining (i) a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm for UAV trajectory control to enhance service coverage and energy efficiency, with (ii) a low-complexity task offloading algorithm for UEs. The framework is explicitly designed to minimize UE energy consumption while promoting fairness in task allocation and data rates. Simulations demonstrate that our approach significantly outperforms state-of-the-art benchmarks, reducing UE energy consumption by 25–30% and improving fairness indices by up to 90%. The proposed system proves scalable and robust, making it suitable for real-time deployment in resource-constrained environments with dynamic workloads.
Joint RF-Gas Sensing for Victim Localization using UAV Networks
Using UAVs has recently emerged as a cost-efficient solution to assist first responders in search and rescue missions. Victims are usually equipped with wireless devices, which makes RF sensing an efficient solution for their localization in disaster situations. Nevertheless, the success of existing methods is highly diminished by the noisy nature of RF measurements. While leveraging recent advancements in lightweight gas sensing, we present in 25 a novel localization approach that efficiently combines RF measurements with victim odor information while accounting for the dynamic nature of measurements' quality.
8.2 Wireless protocols design
Participants: Juan A. Fraire, Oana Iova, Hervé Rivano, Razvan Stanica, Fabrice Valois.
Handover Management in Virtualized Radio Access Networks
The evolution of mobile networks towards more diverse services and open architectures has led to the emergence of mobile network function virtualization. This allows to match the reserved resources for network operation to the actual resources that are needed in the network at a certain place and time. Mobility-related network functions, specifically handover, can also be virtualized in this new paradigm. This virtualization can be facilitated by studying handover behavior at the base station level. In 11, using agglomerative hierarchical clustering, we show the existence of different base station profiles in terms of handovers, including three primary profiles: producer, receiver, and balanced. We also show that the use of these profiles, in addition to the dynamic reconfiguration enabled by virtualization, can reduce reserved resources by more than 50% compared to the current static system.
Prediction-based Discontinuous Reception Mechanism for Extended Reality Applications
Extended reality (XR) applications are characterised by their unique multi-modal traffic pattern. However, XR user equipment (UE) presents significant battery-related challenges. Meanwhile, the discontinuous reception (DRX) mechanism was designed and standardised to extend the UE battery life on cellular networks. The DRX mechanism is based on a number of parameters, and studies focused on modelling its behaviour targeted diverse types of traffic on UMTS, LTE, and 5G NR networks. In this work 45, we examine prediction-based DRX optimisation tailored for XR applications. We design a dynamic DRX optimisation algorithm that utilises predictions of traffic inter-arrival times to select dynamic DRX parameters with two performance metrics: energy efficiency and delay. Using publicly available XR data, we utilised state-of-the-art forecasting tools such as Long Short Term Memory and Gaussian Processes models to design our dynamic DRX solution, and we report an improvement over the energy efficiency obtained by the standard DRX mechanism with minimal extra-delay.
Enhanced LR-FHSS receiver for headerless frame recovery in space–terrestrial integrated IoT networks
Long-Range Frequency Hopping Spread Spectrum (LR-FHSS) is a recent IoT modulation technique designed for communication between low-power ground end-devices and Low-Earth Orbit (LEO) satellites. To successfully decode a frame, an LR-FHSS gateway must receive at least one header replica and a substantial portion of the payload fragments. However, the likelihood of LR-FHSS header loss increases with the number of concurrent transmissions. Moreover, Doppler effects (such as the Doppler shift and the Doppler rate) distort the signals the satellites receive. This work 7 investigates advanced receiver techniques for recovering LR-FHSS frames with lost headers characterized by significant Doppler effects. This work's main contribution is specifying and validating a novel LR-FHSS receiver model for space–terrestrial integrated IoT environments. Obtained simulation results prove that our enhanced LR-FHSS receiver can decode a significant portion of the missing frames, improving the overall throughput achievable by using the legacy LR-FHSS receiver.
Enhancing LR-FHSS Scalability Through Advanced Sequence Design and Demodulator Allocation
The accelerating growth of the Internet of Things (IoT) and its integration with Low-Earth Orbit (LEO) satellites demand efficient, reliable, and scalable communication protocols. Among these, the Long-Range Frequency Hopping Spread Spectrum (LR-FHSS) modulation, tailored for LEO satellite IoT communications, sparks keen interest. This work 8 presents a joint approach to enhancing the scalability of LR-FHSS, addressing the demand for massive connectivity. We deepen into Frequency Hopping Sequence (FHS) mechanisms within LR-FHSS, spotlighting the potential of leveraging Wide-Gap sequences. Concurrently, we introduce two novel demodulator allocation strategies, namely“, Early-Decode" and “Early-Drop," to optimize the utilization of LoRa-specific gateway decoding resources. Our research validates these findings through extensive simulations, providing a detailed analysis of the scalability potential of LR-FHSS in IoT environments. The results demonstrate that the proposed strategies can boost decoding capacity by up to 50% in certain configurations.
From the City to the Clouds: An Experimental Performance Evaluation of LR-FHSS
This work comprehensively evaluates Long-Range Frequency Hopping Spread Spectrum (LR-FHSS) modulation for urban and aerial IoT scenarios, comparing it with the established Long Range (LoRa) modulation in LoRaWAN networks. LR-FHSS offers a promising alternative to LoRa by efficiently utilizing the available spectrum, enhancing device capacity, and minimizing collisions in dense deployments. Using a range of performance metrics, including Packet Delivery Ratio (PDR) and Received Signal Strength Indicator (RSSI), we experimentally assess in 41 LR-FHSS's performance across varied data rates, payload lengths, and coding rates. Our urban and elevated balloon based measurements provide the first real-world insights into LR-FHSS's potential for dense urban networks and sparse aerial applications. Our results reveal conditions where LR-FHSS outperforms LoRa, offering deployment guidelines for Internet of Things (IoT) networks that require high reliability and scalability.
FLoRaSat 2: Simulating Cross-Linked Direct-to-Satellite IoT LEO Constellations with Joint Access and Routing Evaluation
We present in 5 FLORASAT 2, an open-source, event-driven simulator based on OMNET++. The first version of FLORASAT focused on device-to-satellite communication, providing a unique tool to study LoRa/LoRaWAN-based DtS-IoT systems. The present work advances FLORASAT 2 into a full end-to-end simulation framework by integrating Medium Access Control (MAC) protocols with constellation-grade routing models, including constellation creation, dynamic ISL topology control, and a sandbox for benchmarking routing algorithms such as Directed, DDRA, and DiscoRoute. Notably, it introduces K-MAC, a repetition-based MAC scheme designed to improve resilience under Doppler effects, congestion, and intermittent visibility, while expanding the satellite and device modules to support multiple MAC protocols beyond LoRaWAN. To the best of our knowledge, FLORASAT 2 is the only open-source simulator capable of jointly evaluating access and routing layers for constellation-grade DtS-IoT networks. Through extended benchmark scenarios on Starlink-and Iridiumlike constellations, we demonstrate how the integration of MAC and routing enables a more realistic and holistic assessment of network performance, positioning FLORASAT 2 as a versatile platform for the design and optimization of next-generation satellite IoT systems.
Performance evaluation of the interference between LoRa and Wi-Fi transmissions
Recently, the LoRa (Long-Range) modulation technique has been extended from the sub-GHz band to the 2.4 GHz Industrial, Scientific, and Medical (ISM) band, enabling the construction of a LPWAN that benefits from global interoperability without duty-cycle limitations. However, the coexistence of LoRa with the other wireless technologies of the 2.4 GHz ISM band is a challenging question. In this work 6, we make the first performance evaluation of the interference between LoRa and Wireless Fidelity (Wi-Fi) transmissions, by analyzing multiple parameters: LoRa channel occupancy, deployment topology, LoRa physical layer parameters, and the frequency channels used. We also perform simulations to extend our experimental results to other configurations. The performance evaluation is achieved using a generic methodology that can be applied to other wireless technologies. Finally, we provide recommendations for the use and deployment of LoRa that will improve its coexistence with Wi-Fi.
A-SABR: The Adaptive Library for Schedule-Aware Bundle Routing
Deep space communications face long delays and disruptions, making Delay-Tolerant Networking (DTN) and specialized routing essential. To address this, the CCSDS published the Schedule-Aware Bundle Routing (SABR) standard, built on the Contact Graph Routing (CGR) algorithm. Yet, over a decade of CGR development has introduced complexity and fragmentation, hindering prototyping and benchmarking. This work 32 presents the Adaptive Library for Schedule-Aware Bundle Routing (A-SABR), an extensible Rust-based library for research and operations involving SABR/CGR. A-SABR supports rapid development and evaluation of routing strategies through a safe, modular design, and includes a broad set of existing CGR variants. It bridges the gap between flexible prototyping and reliable benchmarking, accelerating innovation in DTN routing. To illustrate its adaptability, we introduce new methods developed with A-SABR: a routing algorithm stamped VolCgr (Volume-CGR), a shortest-path-tree-based pathfinding for contact graphs, and additional options for volume management.
Probabilistic-Aware Satellite Constellation Scheduling for Integrated TN-NTN Operations
This work presents a framework for integrated NTN operations that incorporates stochastic traffic modeling into satellite scheduling, enabling a more flexible and realistic approach to resource management in NTNs. By leveraging statistical traffic models based on the central limit theorem, the proposed method accounts for traffic uncertainty and embeds it directly into the scheduling process. A key concept introduced is schedule certainty, which quantifies the reliability of a schedule under uncertain input conditions and serves as both a decision variable and an optimization parameter. This novel approach in 13 is exemplified through the Constellation Management System framework, extended with a data generation uncertainty model to showcase its practical implementation and benefits. Results demonstrate that probability-aware scheduling achieves a tightly controlled certainty level aligned with operator-defined thresholds, providing higher certainty levels for equivalent performance metrics.
Energy Efficient and Resilient Task Offloading in UAV Assisted MEC Systems
Unmanned aerial vehicle (UAV)-assisted Mobile Edge Computing (MEC) presents a critical trade-off between minimizing user equipment (UE) energy consumption and ensuring high task execution reliability, especially for mission-critical applications. This work proposes a novel reinforcement learning (RL)-based framework that intelligently distributes computational tasks among UAVs and base stations (BSs). We introduce in 15 a permutation strategy that redundantly assigns tasks to multiple edge servers, guaranteeing execution continuity even under partial system failures. An RL agent optimizes the offloading process by leveraging network state information to balance energy consumption with system robustness. Extensive simulations demonstrate the superiority of our approach over state-of-the-art benchmarks. Notably, our proposed framework sustains average UE energy levels above 75% under high user densities, exceeds 95% efficiency with more base stations, and maintains over 90% energy retention when 20 or more UAVs are deployed.
8.3 Network data analysis
Participants: Walid Bechkit, Juan A. Fraire, Hervé Rivano, Razvan Stanica.
On-Device Deep Learning: Survey on Techniques Improving Energy Efficiency of DNNs
Providing high-quality predictions is no longer the sole goal for neural networks. As we live in an increasingly interconnected world, these models need to match the constraints of resource-limited devices powering the Internet of Things (IoT) and embedded systems. Moreover, in the era of climate change, reducing the carbon footprint of neural networks is a critical step for green artificial intelligence, which is no longer an aspiration but a major need. Enhancing the energy efficiency of neural networks, in both training and inference phases, became a predominant research topic in the field. Training optimization has grown in interest recently but remains challenging, as it involves changes in the learning procedure that can impact the prediction quality significantly. This work 2 presents a study on the most popular techniques aiming to reduce the energy consumption of neural networks training. We first propose a classification of the methods before discussing and comparing the different categories. In addition, we outline some energy measurement techniques. We discuss the limitations identified during our study as well as some interesting directions, such as neuromorphic and reservoir computing (RC).
SNOW: A Split Reinforcement Learning Approach for Energy Efficiency in Tactical Network Slicing
In 9, we tackle a joint slice activation/deactivation and user association problem with the aim of studying trade-offs between energy efficiency and user quality of service. To solve the problem, we introduce our original approach: a split reinforcement learning-based energy-efficient slicing deployment algorithm, namely SNOW. SNOW divides the deep neural network into multiple sections, where the front-end part of the model is trained over multiple user devices and then the back-end part of the model is trained by the central nodes, without sensitive data sharing. Extensive simulation results reveal that the proposed scheme is superior to the considered benchmarks in improving energy efficiency while maintaining network performance.
HGC-LSTM: A Graph Neural Network-based Model for HO Forecasting in Mobile Networks
Ensuring seamless connectivity, mobility, and optimal user experience in such a dynamic environment is more complex than ever. In this context, effective user mobility management through handovers (HOs) emerges as a critical task. Poor HO management can lead to issues such as increased latency, network congestion, and elevated operational costs. Against this backdrop, our work focuses on the problem of HO forecasting, aiming to predict HOs among base stations over time. To address this challenge, we introduce in 17 the HO Graph Convolutional Long Short-Term Memory (HGC-LSTM) neural network forecasting approach. This innovative methodology incorporates Graph Neural Networks (GNNs) and Long Short-Term Memory (LSTM) networks to capture spatio-temporal dependencies and correlations among neighboring pairs of base stations during the forecasting process. Our evaluation, conducted on a real-world dataset, demonstrates that integrating HGC-LSTM into a dynamic HO resource allocation framework can offer substantial advantages to a mobile operator when contrasted with a conventional static approach.
On the role of machine learning in satellite internet of things: A survey of techniques, challenges, and future directions
The drive towards an interconnected world via satellites is reshaping the landscape of communication technologies. This survey comprehensively reviews studies in the Satellite Internet of Things (SIoT) domain, focusing on the role of Machine Learning (ML) techniques. Indeed, the global data collection scale in SIoT is ideally suited for data-intensive and sophisticated ML approaches. We highlight the innovative use of ML to address specific SIoT challenges, aiming to identify current trends, methodologies, and outcomes. We considered theoretical, practical, and experimental research, organizing existing publications into a new taxonomy that intersects ML and SIoT categories. Our taxonomy reveals that Deep Learning (DL), Reinforcement Learning (RL), and Federated Learning (FL) are widely applied to address radio access schemes, resource and network management, and application-specific issues. This survey 4 identifies critical gaps in current research on ML applications in SIoT, such as the lack of differentiation between space-based and ground-based processing, insufficient integration of SIoT-specific metrics, and the oversight of limited computational resources on orbiting satellites. These issues raise concerns about the feasibility and efficiency of proposed solutions. We propose promising research directions based on the derived insights to effectively bridge the gap between ML researchers and industrial SIoT entities.
Understanding Urban Behavior: Information Theory Insights from WhatsApp Traffic Analysis
Instant messaging represents the most popular digital service worldwide, and WhatsApp is the most used app of this kind. By studying WhatsApp traffic, we can gain major insight into both human behavior and network infrastructure needs. This work 39 presents a unique analysis of mobile networks using WhatsApp uplink traffic. We apply information theory metrics such as Shannon Permutation Entropy, Statistical Complexity, and the Causality Complexity-Entropy Plane to understand specific network patterns, usage behaviors, and areas where users are more likely to engage in online conversations. We also demonstrate how these metrics can be used as features for machine learning techniques such as the K-means algorithm, showing they can be used to identify regions with similar patterns in the WhatsApp network traffic.
Experimental Analysis of Energy Consumption in Video Streaming Services
Video streaming represents the most popular service on the Internet in terms of traffic volume, and video content is increasingly consumed by users on mobile devices. Therefore, in this study, we design and conduct an experimental campaign to measure the energy consumption of mobile devices and their wireless network modules in the context of video streaming services. We compare in 1 the energy consumption for five video streaming platforms over multiple radio access technologies (WiFi, 3G, 4G, and 5G), using commercial networks as well as a private cellular network set-up. Our results show a significant variation in terms of energy consumption between video platforms, with very different behaviors appearing at the inspection of the collected traces. We also show that the 5G technology represents, at least for now, the most energy-hungry solution at the user level. Finally, we test the different video quality options available for the different platforms, showing once again a very heterogeneous behavior in terms of power consumption patterns.
A Comparison of Energy Consumption in Voice Call Services
Voice call services remain the fundamental use case for mobile phones, even as modern smartphones have grown into sophisticated computing platforms. While prior work has addressed the general power behavior of mobile devices, little attention has been paid to the specific energy footprint of voice services at a component level. In this work, we address this gap by performing fine-grained energy measurements, isolating the power rail of the radio frequency (RF) module within commercial smartphones. Our analysis in 24 compares total device and RF-only energy consumption across multiple voice call technologies under controlled conditions. We demonstrate that the accuracy of measuring energy consumption in voice call technology, when based only on the total device consumption, can distort conclusions and lead to incorrect analyses.
9 Bilateral contracts and grants with industry
Participants: Walid Bechkit, Juan A. Fraire, Oana Iova, Hervé Rivano, Razvan Stanica, Fabrice Valois.
- SPIE (2016-2027): Agora has been involved in two consecutive chairs with SPIE. The first was about IoT, and Razvan Stanica was responsible for the “cognitive networks” research axis. The followup is about AI applied to data flows and network infrastructure analysis. Walid Bechkit is co-responsible of the "embedded AI" research axis. Razvan Stanica is co-responsible of the "data-oriented protocols and infrastructures" research axis. Furthermore, SPIE is funding Audrey Nageotte's CIFRE PhD thesis (started in 2024) on "root cause analysis in network anomaly detection".
- Eiffage (2021-2025): A bilateral collaboration with Eiffage Energie Systèmes on the energy consumption measurement and modeling in 4G and 5G cellular networks.
- Thalès (2024-2025): A bilateral contract with Thalès SIX GTS France in the SCAF project, on Dynamic neighborhood discovery in 3D networks.
10 Partnerships and cooperations
10.1 International initiatives
10.1.1 Associate Teams
DORSAL-IoT
Participants: Juan A. Fraire, Oana Iova, Hervé Rivano, Fabrice Valois.
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Title:
Downlink Optimization for Robust Direct-to-Satellite LoRaWAN IoT
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Duration:
January 2025 – December 2027
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Partners:
- Cesar Azurdia (Universidad de Chile)
- Miguel Gutiérrez Gaitán (Pontificia Universidad Católica de Chile)
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Summary:
DORSAL-IoT aims to develop robust downlink protocols for LoRaWAN-based Direct-to-Satellite IoT communications. The project addresses key challenges in gateway selection, packet scheduling, and optimization for resource-constrained satellite networks.
D3-CONNECT
Participants: Juan A. Fraire.
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Title:
Democratized Direct-to-Device Satellite Communication Networks
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Duration:
January 2025 – December 2027
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Partners:
- Prof. Sylvia Ratnasamy (UC Berkeley – NetSys Group)
- Prof. Scott Shenker (UC Berkeley – NetSys Group)
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Summary:
D3-CONNECT is focused on revolutionizing satellite communication networks. Our mission is to democratize direct-to-device satellite communications by developing inclusive architectures that enable both large and small space actors to participate in the emerging D2D ecosystem. We aim to break down barriers to entry and create a more equitable space communication infrastructure.
10.1.2 STIC/MATH/CLIMAT AmSud projects
DORSAL-IoT
Participants: Oana Iova, Juan A. Fraire, Hervé Rivano, Fabrice Valois.
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Title:
Downlink Optimization for Robust Direct-to-Satellite LoRaWAN IoT
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Program:
STIC-AmSud
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Duration:
January 2025 – December 2026
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Partners:
- Cesar Azurdia (Universidad de Chile)
- Marcos Diaz (Universidad de Chile)
- Miguel Gutiérrez Gaitán (Pontificia Universidad Católica de Chile)
- Diego Dujovne (Universidad Diego Portales)
- Samuel Montejo Sánchez (Universidad Tecnológica Metropolitana)
- Richard Demo Souza (Universidade Federal de Santa Catarina)
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Summary:
DORSAL-IoT brings together experts from France, Chile, and Brazil to develop robust downlink protocols for LoRaWAN-based Direct-to-Satellite IoT communications. The project addresses key challenges in gateway selection, packet scheduling, and optimization for resource-constrained satellite networks.
10.2 International research visitors
Inria International Chair
Dr. Catherine Rosenberg, a professor in the Department of Electrical and Computer Engineering at the University of Waterloo since 2004, holds an Inria International Research Chair in the AGORA team for the 2025-2030 period.
Other international visits to the team
As part of the DORSAL-IoT project, the Agora team hosted during a week the brazilian and chilean partners of the project (September 22-26)
10.3 European initiatives
10.3.1 H2020 projects
Program Horizon 2020 Research and Innovation Staff Exchange (RISE)
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Project acronym:
MISSION
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Project title:
Models in Space Systems: Integration, Operation, and Networking
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Duration:
2021–2025 (4 years)
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Coordinator:
University of Twente, Netherlands
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Other partners:
RWTH Aachen University (Germany), Saarland University (Germany), Universidad Nacional de Córdoba (Argentina), Universidad Nacional de Río Cuarto (Argentina), D3TN (Germany), GOMspace (Luxembourg), Ascentio (Argentina), INVAP (Argentina), Skyloom (Argentina), Institute of Intelligent Software, Guangzhou (China).
Abstract
Spacecraft must work robustly in the presence of uncertainties such as random hardware faults, operator mistakes, space debris, and radiation. Classic space missions address uncertainty via large safety margins and built-in redundancy, leading to a spiral of increasing cost and complexity. A recent trend is the small-business commercialisation of space using commercial-off-the-shelf components for networked constellations of small satellites. This "New Space" approach reduces component weight, size, price, and lead time, and makes innovation increasingly driven by software. This pertains especially to resource management and data handling, while simpler components and new interactions increase uncertainty, and come with less reliable parts. Thus, overall mission connectivity, efficiency, dependability and safety in the New Space needs to be achieved on a system level - for which there is no systematic approach yet. This is partly rooted in the empirical focus of many teams, and partly in a lack of easy-to-use methods to model, analyse, and guarantee system-level dependability. This interdisciplinary project sets out to solve this space engineering problem by exploiting highly advanced techniques from the forefront of computing science research, especially model-based algorithmics. We strive for sound and efficient software tools for the development of dependable, networked, and resource-aware New Space missions. For this, the MISSION project will develop an integrated model-based technology to establish and maintain system-level properties of critical space mission parameters. A strong consortium of excellent academic and industrial partners in Europe, Argentina and China have agreed on a joint research and knowledge-sharing agenda that will foster a shared culture of research and innovation, to finally deliver an ecosystem of easy-to-use methods and software tools to the New Space industry.
10.3.2 Other European programs/initiatives
Program CHIST-ERA 2020
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Project acronym:
ECOMOME
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Project title:
Measurement and Optimisation of Energy Consumption in Cellular Networks
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Duration:
02/2022–01/2025
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Coordinator:
INSA Lyon
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Other partners:
ETS Montréal (Canada), IMDEA (Madrid, Spain), Politehnica University of Timisoara (Romania).
Abstract
This project addresses the problem of accurately modelling and optimising the energy consumption of a mobile network, with a focus on 4G and 5G technologies. This will be achieved through three main research axes. The first contribution will be represented by the first independent measurement study of energy consumption in a mobile network. The second objective of the project is to use this measurement data in order to design accurate energy consumption models for mobile networks. Finally, the project also targets the proposal of energy efficient networking solutions. Indeed, the measurement data and the energy consumption models will allow us to detect the most energy-hungry phases in a mobile network. To reduce their impact, we will propose network intelligence solutions, which are based on observing the traffic transported by the network, detecting whenever the network settings are over-consuming, and adapting the network configuration with energy efficiency metrics in mind.
10.4 National initiatives
- ANR CoCo5G (Traffic Collection, Contextual Analysis, Data-driven Optimisation for 5G), 2023-2027, accepted in 2022
- Participants: Hervé Rivano, Razvan Stanica.
- The partners in this project are: Thales (leader), Orange, CNAM, Inria Agora, IMDEA Networks.
- Summary: The objective of CoCo5G is to collect the first-of-its-kind longitudinal nationwide measurements dataset combining 4G and 5G data traffic. This dataset will then be used for an extensive analysis of the evolution (in France) and the dynamics of 5G traffic for various mobile services usages. This will represent a unique opportunity for the evaluation and tailoring of existing analytics for classification, prediction and anomaly detection within real-world high-detail per-service mobile network data. Finally, CoCo5G targets to demonstrate the integration of data analytics within next-generation cognitive network architecture in three practice case studies: energy-prudent 5G NR control, URLLC service support, and automated anomaly response in edge computing.
- ANR JCJC Doll (Efficient DOwnLink Communication for Increased LoRaWAN Capacity), 2022-2025 (accepted in 2021)
- Participants: Alexandre Guitton, Gwendoline Hochet Derevianckine, Oana Iova (leader), Fabrice Valois.
- Summary: The goal of this project is to propose a downlink strategy that will unleash the full potential of LoRaWAN networks and push the deployment of new applications that until now could not properly take advantage of the downlink communication available in LoRaWAN. In order to increase network capacity under confirmed traffic, while maintaining a reliable uplink communication and a low energy consumption for the end devices, we set the following objectives: i) understand and quantify the consequences of overlapping uplink and downlink communications, ii) evaluate and improve gateway selection algorithm for downlink communication, and iii) propose an energy efficient scheduling for handling acknowledgements.
- ANR JCJC Dron-Map (Réseau de drones pour le suivi de panaches de pollution dans les situations d'urgence), 2021-2025 (accepted in 2021)
- Participants: Mohamed Sami Assenine, Walid Bechkit (leader), Ichrak Mokhtari, Hervé Rivano, Alexandros Sidiras Galante.
- Summary: The DRON-MAP project focuses on the use of cooperative UAV networks for pollution plume monitoring in emergency situations (industrial accidents, natural disasters, deliberate terrorist releases, etc.). The deployment of a UAV network in these situations face different scientific and technical challenges such as taking into account the strong plume dynamics, the timely data analysis, the reliable communication and coordination between UAVs and the planning of optimal trajectories. The objective of DRON-MAP project is to address these challenges while proposing a new global and systemic approach. Based on reliable communications and coordination between drones, our approach will federate an instantaneous estimation and a prediction of the plume evolution with efficient anticipatory algorithms of optimal path planning. A network testbed of few communicating UAVs will be set up in order to assess real-world feasibility and performance at a small scale.
- ANR STEREO (Space-Terrestrial Integrated IoT), 2023-2027, accepted in 2022
- Participants: Juan A. Fraire, Oana Iova, Fabrice Valois.
- The partners in this project are: Inria (leader of the project), IRIT / ENSEEIHT (UMR CNRS 5505), Kinésis, LAAS (CNRS UPR 8001), LIG / UGA (UMR CNRS 5217).
- Summary: The objective of this project is to achieve a Space-Terrestrial Integrated Internet of Things (STEREO) network, in which IoT devices can seamlessly hook to gateways on ground or directly to low-Earth orbit (LEO) satellites when no network infrastructure is present. The feasibility and expected performance will be assessed by objectives described in this section: O.1) defining new network architectures, O.2) evaluating the enabling IoT technologies, O.3) designing the software components, and O.4) prototyping the hardware modules.
Programmes et Equipements prioritaires de rechercheche (PEPR)
- PEPR NF
- Project title: Networks of the Future
- Duration: 2023 - 2030
- Budget: 65M€
- Coordinators: CEA, CNRS, IMT
- Inria participants: Inria project-teams AGORA, AIO, COATI, DIANA, DYOGENE, ERMINE, FUN, MARACAS, NEO, RESIST, TRIBE
- Summary: The 5G network and the networks of the future represent a key issue for French and European industry, society and digital sovereignty. This is why the French government has decided to launch a dedicated national strategy. One of this strategy's priority ambitions is to produce significant public research efforts so the national scientific community contributes fully to making progress that clearly responds to the challenges of 5G and the networks of the future. In this context, the CNRS, the CEA and the Institut Mines-Télécom (IMT) are co-leading the '5G' acceleration PEPR to support upstream research into the development of advanced technologies for 5G and the networks of the future. Inria is involved into 8 research projects over the 10 supported by the program, with the participation of 11 teams of the theme “Networks and Telecommunications” and the coordination of the PC9-Founds.
- Agora is contributor to the following PCs: PC2 NAI (Networks Architecture and Infrastructure and Networks, Cloud, and Sensing Convergence), PC6 FITNESS (From IoT breakthroughs to Network Enhanced ServiceS), PC7 JEN (Just Enough Network) and DONUTS project.
- DONUTS : Project title: Design and Modeling of Multi-Scale and Multi-Technology Future Networks: From 5G/6G Cellular to Non-Terrestrial Networks
- Duration: 2025 - 2029
- Coordinators: IRIT
- AGORA participation led by Fabrice Valois
- Summary: At the heart of DONUTS is the design and construction of a space-air-ground continuum to enable continuous connectivity and seamless transitions across different network segments. This involves optimizing network function placement and efficient resource management across diverse technologies and scales.
- PEPR MOBIDEC
- Project title: Digitalisation et Décarbonation de Mobilités
- Duration: 2023 - 2030
- Budget: 20M€
- Coordinators: IFP Energies nouvelles (IFPEN), Université Gustave Eiffel
- Inria participants: Agora, COATI, FUN, TRiBE
- Summary: The goal of PEPR MOBIDEC is to develop sober, sovereign and resilient mobility, by placing the collection, analysis and processing of mobility data at the heart of its work. It aims to understand and anticipate the mobility behaviours of goods and people, to facilitate the interpretation and processing of data, and to offer decision-making tools to simulate the impact of public policies in advance, or to assess the perJnence of a new transport offer.
- Agora is contributor to the following PC: PC3 MOB-SCI-DATA FACTORY
- PEPR CLOUD
- Project title: Development of advanced cloud technologies
- Duration: 2023-2030
- Budget: 56M€
- Coordinators: CEA, Inria
- Inria participants: at least Agora :)
- Summary: The aim is to support the development of French Cloud players in four key areas: developing innovative Cloud and Edge Computing solutions, creating shared data spaces, training and retraining human resources, and supporting research, innovation and technology maturation.
- Agora is contributor of the following PC: PC8 SILECS (Super Infrastructure for Large-Scale Experimental Computer Science).
10.5 GDR CNRS RSD
Communication networks, working groups of GDR ASR/RSD, CNRS (ongoing participation since 2006):
Oana Iova is member of the steering committee of the GDR RSD and also co-chair of the mentoring activity (e.g., seminars). Razvan Stanica is member of the scientific council of the GDR RSD. Fabrice Valois is member of the steering committee of the GDR RSD and also co-chair of the Networking axis of the GDR RSD. All the members of Agora are regular participants to the GDR RSD.
10.6 Regional initiatives
INSA-Lyon - ATMO-Aura Chair, L'air un enjeu de santé et d'innovation, une mobilisation citoyenne (2020-Present):
Walid Bechkit and Hervé Rivano have been deeply involved in this Chair proposal and its animation.
11 Dissemination
Participants: Walid Bechkit, Ahmed Boubrima, Juan A. Fraire, Oana Iova, Hervé Rivano, Razvan Stanica, Fabrice Valois.
11.1 Promoting scientific activities
11.1.1 Scientific events: organisation
General chair, scientific chair
- Juan A. Fraire is chairing SPACE, a new Research activity at IETF.
- Juan A. Fraire was General Chair of the Space-Terrestrial Internetworking Workshop (STINT) at the WISEE 2025 conference.
- Razvan Stanica was General Chair for the NetMob Data Challenge 2025.
Member of the organizing committees
- Razvan Stanica was Tutorials Chair for the conference NoF 2025.
11.1.2 Scientific events: selection
Member of the conference program committees
- Juan A. Fraire was member in the TPC of : IEEE RAIN4C 2025 and Cores 2025.
- Oana Iova was member in the TPC of: IEEE Globecom 2025, WiMob 2025, MedComeNet 2025, VTC Spring 2025, IFIP TMA 2025, RAGE workshop 2025 (ACM CPS-IoT-Week), CoRes 2025, Slices-FR Summer School 2025.
- Razvan Stanica was member in the TPC of :IFIP Networking 2025, IEEE ICC 2025, IEEE VTC Spring 2025, IEEE MeditCom 2025, IFIP WD 2025, WONS 2025, WiMon 2025, ICIN 2025, NoF 2025.
- Fabrice Valois was member in the TPC of: IEEE Globecom 2025, IEEE ICC 2025, IEEE Infocom Demo 2025, IEEE Infocom NetRobiCS 2025, IEEE ISCC 2025, IEEE MeditCom 2025, IEEE PIMRC 2025, IEEE VTC Fall 2025, IEEE WCNC 2025, IEEE WiMob 2025, and the French LPWAN Days 2025.
11.1.3 Invited talks
- During his one-week visit to the Czech Technical University in Prague in June 2025, within the Multi-Robot Systems Group led by Dr. Martin Saska, Walid Bechkit gave a seminar entitled “From Environmental Monitoring with Low-Cost Wireless Sensor Networks to Energy-Efficient On-Device Deep Learning”.
- Walid Bechkit was also invited to give a seminar entitled “From Environmental Monitoring with Low-Cost Wireless Sensor Networks to Energy-Efficient On-Device Deep Learning” at ERIC Laboratory, Lyon in March 2025.
- As part of the 3rd DORSAL-IoT Workshop, Oana Iova gave a keynote talk on terrestrial and satellite communications for the Internet of Things in November 2025 at Pontificia Universidad Católica de Chile.
- Juan A. Fraire and Oana Iova gave a keynote talk on the challenges of terrestrial and satellite communications for the Internet of Things in November 2025 at Inria Chile.
- As part of NTN Days 2025, Juan A. Fraire gave a talk on Unraveling Temporal Challenges in Space Networking in October 2025 in Toulouse.
- Juan A. Fraire presented his recent works at multiple occasions in his recent vists to Berkeley (June 2025, 10 days), Madrid (July 2025, 7 days), and Montreal (Nov 2025, 5 days).
- As part of the 3rd DORSAL-IoT Workshop, Hervé Rivano gave a keynote talk on distributed geolocalization using broadcast wireless communication for ranging in November 2025 in Santiago (Chile).
- Razvan Stanica was invited in May 2025 to give a keynote talk on the Spatio-Temporal Analysis of Mobile Traffic Data at the SACI 2025 conference in Timisoara.
- Fabrice Valois was invited speaker at Univerité Ouverte, Université Lyon 1, to talk about the evolution of communication technologies, April 2025.
11.1.4 Leadership within the scientific community
- Juan A. Fraire is a member of the board of the Interplanetary Networking Special Interest Group (IPNSIG).
- Juan A. Fraire is an academic stakeholder of the Dynamic Coalition on the Interplanetary Internet in the Internet Governance Forum (IGF).
- Juan A. Fraire is now the chair of the SPACE RG at IETF.
- Oana Iova is a Guest Editor for IEEE Journal of Selected Areas in Sensors “Emerging Technologies in Sensor Networks II”, 2025-2026.
- Oana Iova is in charge of the mentorship actions (e.g., seminars) for the GDR RSD (since 2021).
- Hervé Rivano is a member of the scientific council of France Ville Durable since 2021.
- Hervé Rivano is a member of the steering committee of the Science Po Lyon chair Transformation de l'action publique, since 2019.
- Razvan Stanica is a member of the scientific council of the GDR RSD (since 2022).
- Fabrice Valois is the chair of the scientific committee of the Labex IMU (since 2022).
- Fabrice Valois is a member of the steering committee of the GDR RSD (since 2022).
- Fabrice Valois is a co-chair of the Networking axis of the GDR RSD (since 2022).
- Fabrice Valois is a member of the steering committee of the LPWAN Days (since 2023).
- Fabrice Valois is a member of the COURSE, which is in charge of identifying and defining use cases, applications, and scenarios for the national testbed SLICE-FR (networking and cloud), since 2023.
11.2 Teaching - Supervision - Juries - Educational and pedagogical outreach
Bachelor and License
- Walid Bechkit, Introduction to wireless sensor networks, 70h, L2, INSA Lyon.
- Ahmed Boubrima, IP Networks, 24h, L3, Telecom. Dpt. INSA Lyon.
- Ahmed Boubrima, Medium Access Control, 20h, L3, Telecom. Dpt. INSA Lyon.
- Oana Iova, IP Networks, 12h, L3, Telecom. Dpt. INSA Lyon.
- Oana Iova, Computer Networks – Advanced notions, 20h, L3, INSA Lyon.
- Oana Iova, Network Automation Project in GNS3, 20h, L3, Telecom. Dpt. INSA Lyon.
- Oana Iova, Network routing protocols, 34h, L3, Telecom. Dpt. INSA Lyon.
- Hervé Rivano, Algorithms and programming, 64h, L1–L2, INSA Lyon.
- Hervé Rivano, Programming robot control, 20h, L2, INSA Lyon.
- Razvan Stanica, Internet Metrology, 16h, L3, Telecom. Dpt. INSA Lyon.
- Fabrice Valois, IP Networks, 24h, L3, Telecom. Dpt. INSA Lyon.
- Fabrice Valois, Medium Access Control, 38h, L3, Telecom. Dpt. INSA Lyon.
Master
- Walid Bechkit, Performance evaluation of telecom networks, 30h, M1, Telecom. Dpt. INSA Lyon.
- Walid Bechkit, Wireless networks: architecture and security, 60h, M2, Telecom. Dpt. INSA Lyon.
- Walid Bechkit, Network access control, 6h, M2, Telecom. Dpt. INSA Lyon.
- Walid Bechkit, Wireless networks: architecture and security, 30h, Master Cyber Security, INSA Lyon.
- Walid Bechkit, Network access control, 6h, M2, Master Cyber Security, INSA Lyon.
- Juan A. Fraire, Satellite Communications and Navigation, 32h, M2, Telecom. Dpt. INSA Lyon.
- Juan A. Fraire, Space Informatics, 32h, M2, Saarland University (Germany).
- Juan A. Fraire, Mission Analysis, 12h, M1/M2, Argentinian Space Agency.
- Oana Iova, Internet of Things Technologies, 10h, M2, Telecom. Dpt. INSA Lyon.
- Razvan Stanica, Mobile networks, 30h, M1, Telecom. Dpt. INSA Lyon.
- Razvan Stanica, Content delivery networks (routing protocols), 10h, M2, Telecom. Dpt. INSA Lyon.
- Fabrice Valois, Cellular networks, 18h, M1, Telecom. Dpt. INSA Lyon.
- Fabrice Valois, Performance evaluation of network, 32h, M1, Telecom. Dpt. INSA Lyon.
- Fabrice Valois, Private Cellular Networks, 16h, M1, Telecom, Dpt. INSA Lyon.
Administration and services linked to teaching activities
- Oana Iova is the head of the networking teaching team in the Telecommunications department at INSA Lyon, coordinating all the courses in the networking domain.
- Oana Iova is vice-dean of the International Affairs of INSA Lyon.
- Oana Iova is responsible of the Smart program (international teaching program with Tohoku University and Tokyo University) about Smart Cities.
- Hervé Rivano is the head of the Computer Science discipline in FIMI department of INSA Lyon.
- Hervé Rivano is referent DSI in the FIMI department, INSA Lyon.
- Razvan Stanica is responsible of the research option at the Telecommunications department of INSA Lyon.
- Razvan Stanica was during 2025 the vice-dean of the Telecommunications department of INSA Lyon, in charge of education related affairs.
- Fabrice Valois is in charge of the Humanities course about creative process in Modern Art, Science and technology.
- Fabrice Valois is in charge of the international affairs of the Telecommunications Department since December 2023.
11.2.1 Supervision
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PhD thesis (defended in 2025):
- Zhiyi Zhang, Deployment of mobile base stations in cellular networks, defended in 01/2025.
- Sekinat Yahya, A Study of Energy Consumption Challenges in Extended Reality Services over Cellular Networks, defended in 07/2025.
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PhD thesis (started in 2025):
- Shengcong Zhang, Two-sided mobility management for ground to space cellular networks, since 11/2025.
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PhD thesis (ongoing during 2025):
- Alexander Choquenaira Florez, Big Data and Machine Learning Methods for Direct-to-Satellite Internet of Things, since 03/2024.
- Audrey Nageotte, Root cause analysis in network anomaly detection, since 11/2024.
- Guillermo Benito Calvino, Victim localization in rescue missions using drone networks, since 11/2024.
- Mohammed Sami Assenine, Apprentissage par renforcement pour l'optimisation de la mobilité dans les réseaux de capteurs sans fil : application au suivi de la pollution, since 10/2022.
- Youssef Badra, Measuring and modelling energy consumption in cellular networks, since 03/2022.
- Anais Boumendil, Vers des modèles d'apprentissage automatique à faible consommation d'énergie pour les plateformes à ressources limitées, since 11/2022.
- Diego Maldonado Munoz, Adaptations, Optimizations, and Learning Approaches for Direct-to-Satellite Internet of Things, since 12/2022.
- Carlos Fernandez Hernandez, Optimization of the downlink in LoRaWAN, since 01/2023.
- Geymerson Ramos, 5G networks mobile data analytics, since 05/2023.
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Masters:
- Abdellatif Bendjeddou, from 01/2025 until 06/2025.
- Benoit Coeugnet, from 01/2025 until 06/2025.
- Noe Fregonese, from 07/2025 until 12/2025.
- Nahuel Gomez Raguileo, from 01/2025 until 04/2025.
- Longrui Ma, from 04/2025 until 10/2025.
11.2.2 Juries
- Oana Iova was a a jury member (examiner) of the following PhD defense: Salah Eddine Elgharbi, Performance of Multi-hop Wireless Networks for Maritime Environments, La Rochelle Université, 2025.
- Oana Iova was a a jury member (examiner) of the following PhD defense: Iliar Rabet, Reliable Low-Power Wireless Networks in Dynamic Environments, Mälardalen University, Sweden, 2025.
- Hervé Rivano was president of the PhD defense jury of L. Cheraitia, Conception de modèles pour la coordination des mobilités actives avec le transport ferroviaire, ENTPE, 2025.
- Razvan Stanica was a jury member (rapporteur) of the following PhD defense : S. Mishra, Data-driven exploration of sociological patterns in mobile network traffic demands, Universidad Carlos III de Madrid, Telematic Engineering, 2025.
- Razvan Stanica was a jury member (rapporteur) of the following PhD defense: S. Alsabbagh, Grant-Free Communication in Next-Generation Cellular IoT: Physical Layer-Aware Optimization. Université Paris-Saclay, Sciences des réseaux, de l'information et de la communication, 2025.
- Fabrice Valois was a jury member (rapporteur) of the following PhD defense: Y. Ashengo, Intelligent Task Offloading and Resource Allocation with Multi-access Edge Computing Servers using 5G for Tactile Internet, Université Paris Saclay, 2025.
- Fabrice Valois was a jury member (examiner) of the following PhD defense: A. Le Floch, Méthodes de localisation en intérieur en 5G. Université de Toulouse, Informatique et Télécommunications, 2025.
11.3 Popularization
- Hervé Rivano was invited to talk about "L'open data et le pouvoir citoyen" in the "Rencontres du cycle Où va la ville", Lyon, April 2025.
- Hervé Rivano gave the inauguration talk on "L'innovation va-t-elle sauver la planète ?" at the "Sommet International de l'Innovation des Villes Médianes", Dunkerque, May 2025.
12 Scientific production
12.1 Major publications
- 1 inproceedingsExperimental Analysis of Energy Consumption in Video Streaming Services.WoWMoM 2025 - 26th IEEE International Symposium on a World of Wireless, Mobile and Multimedia NetworksFort Worth (TX), United StatesMay 2025HALback to textback to text
- 2 articleOn-Device Deep Learning: Survey on Techniques Improving Energy Efficiency of DNNs.IEEE Transactions on Neural Networks and Learning Systems2025HALDOIback to text
- 3 miscThe NetMob25 Dataset: A High-resolution Multi-layered View of Individual Mobility in Greater Paris Region.2025HALback to text
- 4 articleOn the role of machine learning in satellite internet of things: A survey of techniques, challenges, and future directions.Computer NetworksJanuary 2025HALDOIback to text
- 5 articleFLoRaSat 2: Simulating Cross-Linked Direct-to-Satellite IoT LEO Constellations with Joint Access and Routing Evaluation.International Journal of Satellite Communications and Networking2025. In press. HALback to text
- 6 articleHate or Love in the 2.4 GHz ISM band: The Story of LoRa® and IEEE 802.11g.ACM Transactions on Internet of Things71November 2025HALback to text
- 7 articleEnhanced LR-FHSS receiver for headerless frame recovery in space–terrestrial integrated IoT networks.Computer Networks257February 2025, 111018HALDOIback to text
- 8 articleEnhancing LR-FHSS Scalability Through Advanced Sequence Design and Demodulator Allocation.IEEE Transactions on Green Communications and Networking2025HALDOIback to text
- 9 inproceedingsSNOW: A Split Reinforcement Learning Approach for Energy Efficiency in Tactical Network Slicing.WoWMoM 2025 - 26th IEEE International Symposium on a World of Wireless, Mobile and Multimedia NetworksFort Worth (TX), United StatesMay 2025HALback to text
- 10 articleICE-CREAM: Multi-agent Fully Cooperative Decentralized Framework for Energy Efficiency in RAN Slicing.IEEE Transactions on Network and Service Management2222025, 1859-1873HALDOIback to text
- 11 inproceedingsHandover Management in Virtualized Radio Access Networks.WoWMoM 2025 - 26th IEEE International Symposium on a World of Wireless, Mobile and Multimedia NetworksFort Worth (TX), United StatesMay 2025HALback to text
- 12 articleQuantifying Edge Server Placement in LEO Constellations: A Comparative Emulation of Space and Terrestrial Cloud.International Journal of Satellite Communications and NetworkingDecember 2025. In press. HALback to text
- 13 articleProbabilistic-Aware Satellite Constellation Scheduling for Integrated TN-NTN Operations.IEEE Open Journal of the Communications Society62025, 3950-3963HALDOIback to text
12.2 Publications of the year
International journals
International peer-reviewed conferences
National peer-reviewed Conferences
Doctoral dissertations and habilitation theses
Reports & preprints
Other scientific publications
Scientific popularization
12.3 Cited publications
- 57 inproceedingsA Comparison of Energy Consumption in Voice Call Services.PIMRC 2025 – IEEE 36th Annual International Symposium on Personal, Indoor and Mobile Radio CommunicationsIstanbul, TurkeySeptember 2025HALback to text
- 58 inproceedingsPoster: Joint RF-Gas Sensing for Victim Localization using UAV Networks.Mobisys25 - 23rd ACM International Conference on Mobile Systems, Applications, and ServicesAnaheim, United States2025, 1-3HALDOIback to text
- 59 inproceedingsFLoRaSat 2: Simulating Cross-Linked Direct-to-Satellite IoT LEO Constellations.12th Advanced Satellite Multimedia Systems Conference and the 18th Signal Processing for Space Communications Workshop (ASMS/SPSC 2025)Sitges, SpainIEEEFebruary 2025, 1-8HALDOIback to text
- 60 articleEnergy Efficient and Resilient Task Offloading in UAV-Assisted MEC Systems.IEEE Open Journal of Vehicular Technology62025, 2236-2254HALDOIback to text
- 61 articleToward Energy Efficiency and Fairness in UAV-Based Task Offloading.IEEE Access132025, 115178-115195HALDOIback to text
- 62 articleHGC-LSTM: A Graph Neural Network-based Model for HO Forecasting in Mobile Networks.Computer Networks270October 2025, 111497HALDOIback to text
- 63 inproceedingsNetwork Size Estimation in DtS-IoT: A LoRaWAN Approach for Satellite Constellations.ICC 2025 - IEEE International Conference on CommunicationsMontreal, FranceIEEEJune 2025, 5506-5511HALDOIback to text
- 64 inproceedingsA-SABR: The Adaptive Library for Schedule-Aware Bundle Routing.WiSEE 2025 - IEEE International Conference on Wireless for Space and Extreme EnvironmentsHalifax, CanadaOctober 2025HALback to text
- 65 inproceedingsUnderstanding Urban Behavior: Information Theory Insights from WhatsApp Traffic Analysis.ICC 2025 - IEEE International Conference on CommunicationsICC 2025 - IEEE International Conference on CommunicationsMontreal, CanadaIEEEJune 2025, 7140-7145HALDOIback to text
- 66 inproceedingsFrom the City to the Clouds: An Experimental Performance Evaluation of LR-FHSS.International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)Lucca, ItalyJune 2025HALback to text
- 67 inproceedingsPrediction-based Discontinuous Reception Mechanism for Extended Reality Applications.CCNC 2025 – IEEE Consumer Communications and Networking Conference, Las Vegas, January 2025.Las Vegas, United States2025HALback to text
- 68 articleJoint Contact Planning for Navigation and Communication in GNSS–Libration Point Systems.IEEE Transactions on Vehicular Technology2025, 1-16HALDOIback to text