7.1.1 Dense LoRaSim

• Name:
  Extension to support dense LPWAN in LoRaSim
• 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.
• Contact:
  Fabrice Valois
• Participants:
  Fabrice Valois, Oana Iova, Hervé Rivano

7.1.2 ELoRa

• Name:
  Extension of ELoRa to support the open source implementation of The Thing Stack
• Keywords:
  LoRaWAN, Downlink scheduling, The Thing Stack
• 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.
• Contact:
  Oana Iova

7.1.3 FLoRaSat

• Name:
  Extension of FLoRa for Direct-to-Satellite IoT
• Keywords:
  Iot, Satellite, LoRaWAN
• 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
• Contact:
  Juan Andres Fraire
• Participants:
  Juan Andres Fraire, Oana Iova, Fabrice Valois

7.1.4 UTOPIA-S

• Name:
  aUTonomous OPtimised aIr quAlity - Software
• Keywords:
  Air Quality, Sensors
• 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.

• 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
• Contact:
  Walid Bechkit
• Participants:
  Walid Bechkit, Ahmed Boubrima, Hervé Rivano

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.

Joint Mapping-Sensing Design of Wireless Sensor Networks for Urban Environmental Monitoring

In 3, we focus on the application of air quality monitoring where wireless sensor networks collect pollution measurements to estimate ground-truth pollution maps. We present UrMapSens, a novel WSN design strategy that aims to optimize the deployment locations of sensor nodes and the estimation of urban pollution maps. Unlike prior work, UrMapSens performs the optimization of both sensor deployment locations and pollution maps' estimation in a joint way. We design our UrMapSens approach based on data assimilation by combining physical models' simulations and expected sensor measurements in the estimation process of air pollution maps. We use enhanced linearization techniques to provide a convex mathematical model based on mixed integer programming, which can be solved efficiently using numerical solvers. To validate UrMapSens in real-life scenarios, we designed an air pollution monitoring platform and used it to collect a dataset of nitrogen dioxide (NO2) concentrations in Lyon, France. Based on the experimentally collected dataset, we perform extensive evaluations of the proposed approach and show that our joint mapping-sensing design outperforms the prior work.

Informative and Communication-Efficient MultiAgent Path Planning for Pollution Plume Monitoring

In 1, we propose an efficient framework for monitoring pollution plumes using sensor-equipped drones. Our approach leverages the power of Reinforcement Learning and Mutual Information to strategically plan drone paths in order to maximize the informativeness of the data collected while minimizing communication costs. We propose a multi-agent Independent Q-Learning scheme, where drones act independently but share a global team reward. The reward is calculated based on both the reduction in plume estimation uncertainty and the communication costs. The proposed framework is adaptable to various problem instances, making it suitable for monitoring diverse physical phenomena. We conduct extensive simulations showing the effectiveness of our approach in achieving high-quality plume monitoring, with an error in variance estimation ranging from 3% to 5% when compared with ground-truth value. The proposed framework is advantageous because it excels not only in providing a good solution but also in inferring it in a reasonable time especially compared to a solution provided by genetic-based heuristics.

On the Use of Mega Constellation Services in Space: Integrating LEO Platforms into 6G Non-Terrestrial Networks

In 6, we propose a framework for integrating Low-Earth Orbit (LEO) platforms with Non-Terrestrial Networks (NTNs) in the emerging 6G communication landscape. Our work applies the Mega-Constellation Services in Space (MCSS) paradigm, leveraging LEO mega-constellations’ expansive coverage and capacity, designed initially for terrestrial devices, to serve platforms in lower LEO orbits. Results show that this approach overcomes the limitation of sporadic and time-bound satellite communication links, a challenge not fully resolved by available Ground Station Networks and Data Relay Systems. We contribute three key elements: (i) a detailed MCSS evaluation framework employing Monte Carlo simulations to assess space user links and distributions; (ii) a novel Space User Terminal (SUT) design optimized for MCSS, using different configurations and 5G New Radio Adaptive Coding and Modulation; (iii) extensive results demonstrating MCSS's substantial improvement over existing Ground Station Networks and Data Relay Systems, motivating its role in the upcoming 6G NTNs.

Towards Optimal Placement of FreeSpace Optical Terminal on the Spacecraft Body

Free-space optical (FSO) links have emerged as a promising solution for enabling high-speed data transfer in networked space systems. These links leverage highly directed optical beams amplified by telescopes that can be oriented using gimbal engines. However, the gimbal's limited swipe range poses a challenge in optimizing the placement of the FSO terminal on the satellite body. This placement directly impacts the feasible contact time, which is constrained by the gimbal motors' degree of freedom and speed as the satellites follow their orbital trajectories. In 8, we address the problem of optimizing the FSO terminal placement to maximize the aggregate effective contact time with the target. First, we formally describe the problem assumptions and perform baseline case studies to gain valuable insights. Next, we define appropriate metrics that capture the contact time performance to evaluate different placement strategies. Our core contributions are two heuristics, simulated annealing, and an evolutionary genetic algorithm to optimize the FSO terminal placement. We finally demonstrate through extensive simulation and analysis that our proposed optimization approaches can significantly improve the baseline contact time by up to 27.7%.

Network Storage Analysis via Semiring Geometry

Interplanetary communications networks will need to handle the delays, disruptions, and disconnections inherent to space communications. The architecture of Delay Tolerant Networking (DTN) provides protocols and strategies to support these communications plans. In the past, routing models in DTN have focused on the forwarding aspects of store-carry-forward. Methods such as Contact Graph Routing, Contact Multigraph Routing, and Probabilistic Routing Protocol using the History of Encounters and Transitivity (PRoPHET) provide solutions for how to choose where to forward bundles through a network. However, these routing models often function bundle-by-bundle allowing them to set aside storage needs for each node. In order to bring our vision of a SSI (Solar System Internet) to reality, we will need to be able to predict and incorporate storage needs that satellites and rovers will require. In 2, we introduce a novel semiring model for contact-based routing protocols that includes a means of determining storage needs. Through proper analysis of the semiring structure, we show how to determine optimal storage structures in satellite networks. In addition, we run our analysis on simulated satellite networks to demonstrate the potential for working with these semiring models in a computational framework. We conclude by indicating future directions for semiring analysis is space communications.

How does Wi-Fi 6 fare? An industrial outdoor robotic scenario

Wi-Fi is a standard off-the-shelf solution for industrial robotics. The IEEE 802.11ax amendment extends it to support the 6 GHz band, 160 MHz bandwidth and bit-rates up to 9.6 Gbps. In 13, we evaluate the performance of Wi-Fi 6 compared to Wi-Fi 5 and Wi-Fi 4. We select 9 physical layers (PHYs) representing different Wi-Fi generations and we evaluate their performance in an industrial shipyard in the presence of high radio frequency interference and metallic obstructions. We deploy setup of a robotic station (STA) and a controller STA with three applications running in parallel: a robotic STA is sending a high throughput stream to a controller, a Robotic Operating System (ROS) application is sending time-critical control commands to the robotic STA, Precision Time Protocol (PTP) keeps synchronizing the clocks between both STAs. We evaluate the performance in terms of three Key Performance Indicators (KPIs): streaming throughput, IP-level delay using PTP, and Application-level delay of ROS control packets. The networks are run in: Short range Line of Sight (LoS), Medium range LoS, Long range None-LoS (NLoS), and Long range mixed settings. We note that depending on the PHY configuration, an older Wi-Fi generation may outperform Wi-Fi 6. We further observe trade-offs between the different PHYs: wide channel PHYs (e.g. 160 MHz) had best throughput reaching up to 900 Mbps while PHYs while 80 MHz or 20 MHz bandwidth achieved as low as 9 ms delay.

The Impact of Downlink Scheduling Policy on the Capacity of LoRaWAN

LoRaWAN is a widely used wireless communication standard for the Internet of Things that enables the collection of measurement data from numerous monitoring applications (such as smart metering, pollution, and asset tracking). Most research work has been focused on the performance of LoRaWAN as a function of the uplink traffic, as this is the most common scenario. Nevertheless, downlink traffic is a fundamental building block of the LoRaWAN standard, and a crucial part of applications such as smart healthcare, where reliability is extremely important. In 5, we study the impact of the downlink traffic and different scheduling policies on the performance of LoRaWAN. We investigate: (i) the impact of an optimal schedule for the downlink traffic, (ii) the choice of the physical layer parameters used to send downlinks to end-devices during the second reception window, and (iii) the choice of the gateway that sends the downlinks. Our results show that even when using an optimal schedule, the presence of downlink traffic reduces the capacity of a LoRaWAN network up to 20%. The most limiting factor is the gateway, due to its duty cycle and half-duplex characteristics.

Downlink Scheduling in LoRaWAN: ChirpStack vs The Things Stack

LoRaWAN is a key enabler for Internet of Things applications, providing long range communication at a low energy consumption. However, extensive use of downlink communication can reduce network capacity and increase uplink loss, as shown in several studies. The network server is responsible for scheduling downlink packets, while respecting strict timing constraints on the end devices and on the gateways. In 35, we present the first evaluation of downlink scheduling implemented by two widely used LoRaWAN network servers: ChirpStack and The Things Stack. Using the ELoRa emulation tool, we inject real LoRaWAN traffic into these network servers and analyze their downlink scheduling algorithms based on defined performance metrics such as reliability and schedule efficiency. Our findings indicate that The Things Stack has a more accurate scheduler, but more conservative, as it delivers less downlink packets. ChirpStack, on the other hand, with its simpler algorithm, performs comparably and even equals The Things Stack as the number of end devices increases.

Traffic control strategies for LPWAN in multigateway environments

In 9, we focus on managing upstream traffic in multigateway Low-Power Wide Area Networks (LPWANs) to support efficient traffic from thousands of nodes. As LP-WANs face challenges such as increased collision probability and network saturation due to node densification, our research introduces a distributed and probabilistic traffic control protocol. This protocol aims to effectively manage network traffic, reduce collisions, and mitigate saturation issues, ensuring better performance and scalability in densely populated IoT environments. The protocol enables nodes to dynamically adapt their traffic to meet application needs, such as transmitting a defined number of measurements (K) within a designated time frame. This adjustment remains unaffected by the node count and network topology, focusing instead on the feedback message's destination to the network nodes, which is crucial for dynamically adapting traffic intensity and reducing collisions. We explore two feedback transmission strategies: a synchronous one, where all gateways transmit feedback simultaneously to all nodes, and a round-robin one, where one gateway at a time sends feedback to nodes within its coverage area. Based on simulation results, our evaluated strategies achieve substantial performance improvements over the Baseline LoRaWAN. Specifically, they demonstrate a network lifetime increase of up to 93.12%, a success rate increase of up to 96.34%, and a packet delivery ratio increase of up to 14.97%.

Trends in LPWAN Technologies for LEO Satellite Constellations in the NewSpace Context

Our work in 10 focuses on a study that applies satellite constellations in Internet of Things (IoT) communications, specifically within low-power wide-area network (LPWAN) technologies in the NewSpace context. It comprehensively categorizes and describes the functionality and typology of low Earth orbits (LEOs), examines the societal impacts of these technologies, and provides an in-depth analysis of IoT communication architectures and protocols utilizing satellites. Additionally, the study identifies and addresses the challenges faced in this domain while highlighting future trends and developments. By collating and synthesizing pertinent information, this research offers a thorough overview of the opportunities and challenges in this evolving field of study.

Comparing Statistical, Analytical, and Learning-Based Routing Approaches for Delay-Tolerant Networks

In delay-tolerant networks (DTNs) with uncertain contact plans, the communication episodes and their reliabilities are known a priori. To maximise the end-to-end delivery probability, a bounded network-wide number of message copies are allowed. The resulting multi-copy routing optimization problem is naturally modelled as a Markov decision process with distributed information. In 15, we provide an in-depth comparison of three solution approaches: statistical model checking with scheduler sampling, the analytical RUCoP algorithm based on probabilistic model checking, and an implementation of concurrent Q-learning. We use an extensive benchmark set comprising random networks, scalable binomial topologies, and realistic ring-road low Earth orbit satellite networks. We evaluate the obtained message delivery probabilities as well as the computational effort. Our results show that all three approaches are suitable tools for obtaining reliable routes in DTN, and expose a trade-off between scalability and solution quality.

A Stability-First Approach to Running TCP Over Starlink

The end-to-end connectivity patterns between two points on Earth are highly volatile if mediated via a Low-Earth orbit (LEO) satellite constellation. This is rooted in the enormous speeds at which satellites in LEO must travel relative to the Earth's surface. While changes in end-to-end routes are rare events in stationary and terrestrial applications, they are a dominating factor for connection-oriented services running over LEO constellations and mega-constellations. In 14, we discuss how TCP-over-constellations is affected by the need for rerouting and how orbital route selection algorithms impact the end-to-end performance of communication. In contrast to the state of the art that primarily optimizes for instantaneous shortest routes (i.e. lowest delay), we propose several algorithms that have route stability and longevity in their focus. We show that this shift in focus comes with vastly improved end-to-end communication performance, and we discuss peculiar effects of the typical TCP-like implementations, taking inspiration from the Starlink constellation in our empirical investigations.

Route Selection in Low-cost Participatory Mobile Sensing of Air Quality

Mobile crowdsensing is a powerful paradigm that takes advantage of low-cost sensors and population density. It allows for large-scale deployments and collection of extensive data, offering a great advantage in multiple fields such as air pollution monitoring, which is a major concern worldwide. Given the mobile nature of the crowd, mobile crowdsensing platforms need to implement adequate route selection/planning solutions to better guide the crowd through the area of interest and maximize the quality of monitoring. In 7, we propose two route selection algorithms that take into consideration the low accuracy of low-cost sensors in order to find the most informative routes. The similarity-based route selection algorithm aims to maximize spatial coverage by reducing overlaps between participant routes. The cluster-based route selection takes advantage of hierarchical clustering to build groups of similar points of the map according to explanatory variables. We compare the proposed solutions to baseline route selection algorithms, and the results show that our solutions allow for a better estimation while being efficient in terms of travel distance.

HeatPulse: Thermal Attacks on Air Pollution Sensors

Air pollution monitoring, especially using miniaturized and low-cost sensors, has been increasingly adopted across many application areas -including chemical and automotive industries, smart cities, and agriculture -to protect public health and comply with environmental regulations. In 12, we demonstrate a new security vulnerability that enables adversaries to remotely spoof low-cost air pollution sensors via long-range and highly localized thermal attacks. Modeling the key attack characteristics, we show how adversaries can exploit the temperature-dependent internal calibration process of air pollution sensors to strategically manipulate sensor measurements through induced heat signals, thereby deceiving the sensors. Using inexpensive laser pointers and commercial Nitrogen Dioxide pollution sensors, we design an evaluation testbed and experimentally show the attack's effectiveness in both indoor and outdoor environments.

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. In 4, we present a study of 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).

A deep reinforcement solution to help reduce the cost in waiting time of securing a traffic light for cyclists

Cyclists prefer to use infrastructures that separate them from motorized traffic. Using a traffic light to segregate car and bike flows, with the addition of bike-specific green phases, is a lightweight and cheap solution that can be deployed dynamically to assess the opportunity of a heavier infrastructure such as a separate bike lane. To compensate for the increased waiting time induced by these new phases, we introduce in 11 a deep reinforcement learning solution that adapts the green phase cycle of a traffic light to the traffic. Vehicle counter data are used to compare the DRL approach with the actuated traffic light control algorithm over whole days. Results show that DRL achieves better minimization of vehicle waiting time at every hours. Our DRL approach is also robust to moderate changes in bike traffic.

10.1.1 Visits of international scientists

• Lucas Santos de Oliveira, assistant professor, from State University of Southwestern Bahia, Brazil, from December 2023 to January 2024.
• Hnin Pann Phyu (ETS Montreal), 3-month PhD visit in 2024.

10.1.2 Visits to international teams

10.2.1 H2020 projects

• Program
  H2020-ICT-2018-2020
• Project acronym: BUGWRIGHT2
• Project title: Autonomous Robotic Inspection and Maintenance on Ship Hulls and Storage Tanks
• Duration:01/2020-03/2025
• Coordinator: GeorgiaTech Lorraine / UMI2958GT-CNRS
• Other partners: 9 academics partners (CNRS, UPORTO, UIB, INSA, RWTH, UNI-KLU, NTNU, UT, WMU) and 11 industrial partners (CETIM, LSL, RBP, BEYE, RINA, GLM, APDL, AASA, TRH, IEIC, DANAOS, SBK).
• Abstract: The objective of BUGWRIGHT2 is to bridge the gap between the current and desired capabilities of ship inspection and service robots by developing and demonstrating an adaptable autonomous robotic solution for servicing ship outer hulls. By combining the survey capabilities of autonomous Micro Air Vehicles (MAV) and small Autonomous Underwater Vehicles (AUV), with teams of magnetic-wheeled craw-lers operating directly on the surface of the structure, the project inspection and cleaning system will be able to seamlessly merge the acquisition of a global overview of the structure with performing a detailed multi-robot visual and acoustic inspection of the structure, detecting corrosion patches or cleaning the surface as necessary - all of this with minimal user intervention.

• Program
  Horizon 2020 Research and Innovation Staff Exchange (RISE)
• Project acronym: MISSION
• Project title: Models in Space Systems: Integration, Operation, and Networking
• Duration: 2021 - ongoing (4 years)
• Coordinator: University of Twente, Netherlands
• Other partners: Netherlands 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 (IISG), 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.

10.2.2 Other European programs/initiatives

• Program
  CHIST-ERA 2020
• Project acronym: ECOMOME
• Project title: Measurement and Optimisation of Energy Consumption in Cellular Networks
• Duration: 02/2022-01/2025 (accepted in 09/2021)
• Coordinator: INSA Lyon
• Other partners: ETS Montréal, Québec, 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.

Programmes et Equipements prioritaires de rechercheche (PEPR)

• Project acronym: 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), and PC7 JEN (Just Enough Network).
• Project acronym: 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
• Project acronym: 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).

11.1.1 Scientific events: organisation

11.1.2 Scientific events: selection

11.1.3 Invited talks

• Juan A. Fraire gave a keynote seminar "On the Role of AI in Satellite Mega-Constellations" at IEEE ICC Workshop on Satellite Mega-Constellations in the 6G Era, Denver, CO, USA, June 2024.
• Juan A. Fraire was invited by Juan Clemente from the Universidad Complutense and NATO to present the IMPACT project at the NATO Workshop, Madrid, 2024.
• Walid Bechkit gave a keynote seminar "Wireless Sensor Networks for Environmental Monitoring: From Measurement to Data Collection and Analysis — Bridging Theory with Practice" at the L2TI lab. scientific day, Paris, 2024.

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).
• 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 chaire "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.

11.1.5 Scientific expertise

• Walid Bechkit was member of the recruitment committee for ATER positions (CITI research laboratory, Telecom department, INSA Lyon) in 2024.
• Walid Bechkit is part of the scientific board of the "Conseil Économique, Social et Environnemental Régional - CESER - ATMO-AURA" since 2022.
• Oana Iova was member of the following recruitment committees:
  • Faculty researcher CRCN, INRAE, 2024
  • Assistant professor position, INSA Lyon, 2024.
• Hervé Rivano was member of the following recruitment committees:
  • Assistant professor position, ENTPE, 2024.
• Razvan Stanica was part of the Hcérés committee for the DAVID laboratory, 2024.
• Fabrice Valois was member of the following assistant professor committees:
  • Assistant professor position, IMT Atlantique, 2024.

11.2.1 Teaching

11.2.2 Supervision

• Masters:
  • Marcos Antonio Rojas Mardones, Experiments on LR-FHSS in an urban scenarios, from 04/2024 until 10/2024. Advisors: Oana Iova and Juan A. Fraire.
  • Moez Zarrouk, Performance evaluation of low-cost air pollution sensors, from 03/2024 until 09/2024, Advisors: Ahmed Boubrima, Hervé Rivano.
  • Mohammed Tiouti, Victim localization in rescue missions using drone networks, from 03/2024 until 09/2024, Advisors: Ahmed Boubrima, Hervé Rivano.
• PhD thesis (defended in 2024):
  • Lucas Magnana, De la ville intelligente à la ville prédictive, application aux modes de transport actifs, defended in 02/2024. Advisors: Nicolas Chiabaut (LICIT, ENTPE / IFSTTAR), Hervé Rivano.
  • Kawtar Lasri, Data collection and distributed spatial coordination in LPWAN networks, defended in 02/2024. Advisors: Oana Iova, Yann Ben Maissa (INPT Rabat, Morocco), Fabrice Valois.
  • Camille Moriot, DDos Attacks and their impacts on the Internet Architecture, defended in 09/2024. Advisors: François Lesueur (IRISA / UBS) Nicolas Stouls (CITI), Fabrice Valois.
  • Gwendoline Hochet Derevianckine,Faisabilité et performances d'un réseau LoRaWAN dans la bande ISM 2.4GHz, defended in 12/2024. Advisors: Alexandre Guitton (UCA), Oana Iova, Baozhu Ning (Semtech), Fabrice Valois.
• PhD thesis (started in 2024):
  • Alexander Choquenaira Florez, Big Data and Machine Learning Methods for Direct-to-Satellite Internet of Things, since 03/2024, Advisors: Juan A. Fraire and Hervé Rivano.
  • Audrey Nageotte, Root cause analysis in network anomaly detection, since 11/2024, Advisor: Razvan Stanica.
  • Guillermo Benito Calvino, Victim localization in rescue missions using drone networks, since 11/2024. Advisors: Ahmed Boubrima, Hervé Rivano.
• PhD thesis (ongoing during 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. Advisors: Walid Bechkit, Hervé Rivano.
  • Youssef Badra, Measuring and modelling energy consumption in cellular networks, since 03/2022. Advisor: Razvan Stanica.
  • Anais Boumendil, Vers des modèles d'apprentissage automatique à faible consommation d'énergie pour les plateformes à ressources limitées, since 11/2022. Advisor: Walid Bechkit Pierre-Edouard Portier (LIRIS / INSA Lyon), Frédéric Le Mouël (CITI / INSA Lyon), Malcolm Egan (CITI / INSA Lyon).
  • Diego Maldonado Munoz, Adaptations, Optimizations, and Learning Approaches for Direct- to-Satellite Internet of Things, since 12/2022. Adivsors: Juan A. Fraire, Hervé Rivano.
  • Sekinat Yahya, Energy consumption optimisation in cellular networks, since 02/2022. Advisor: Razvan Stanica.
  • Zhiyi Zhang, Deployment and management of mobile base stations, since 10/2021. Advisors: Razvan Stanica, Fabrice Valois.
  • Carlos Fernandez Hernandez , Optimization of the downlink in LoRaWAN, since 01/2023. Advisors: Oana Iova, Fabrice Valois.
  • Geymerson Ramos, 5G networks mobile data analytics, since 05/2023. Advisor: Razvan Stanica.

11.2.3 Juries

• Hervé Rivano was the jury president of the following PhD defenses:
  • N. Shakoori, Optimal Dynamic Routing for Urban Networks : a Mathematical Programming Approach with Complete Integration of Traffic Flow Features, INSA LYON / ENTPE, 2024.
  • S. Pelissier, Privacy-preserving communications for the IoT, INSA Lyon, 2024.
• Hervé Rivano was a jury member of the following HDR defenses:
  • W. Bechkit, Contributions to Wireless Sensor Networks for Air Quality Monitoring, CITI/Agora, INSA Lyon, 2024.
  • C. Caillouet, modelisation et Optimisation des réeseaux sans fil : De l'usage des drones aux réeseaux LoRaWAN, I3S/Coati, Université de Nice Sophia Antipolis, 2024.
• Razvan Stanica was a jury member of the following PhD defense:
  • E. Akopyan, Fiabilité de l'architecture réseau des systèmes spatiaux distribués sur essaims de nanosatellites, Université de Toulouse, 2024.
• Fabrice valois was the jury president of the following PhD defense:
  • J. Koteich, Novel Context Aware Opportunistic Data Forwarding Strategy in Wireless Networks, Inria / Université de Lille, 2024.
• Fabrice Valois was a jury member (rapporteur) of the following HDR defense:
  • R. Kacimi, De l'Internet des objets aux réseaux véhiculaires : techniques d'accès, dissémination et délestage de données. Université Paul Sabatier, IRIT, 2024.

International journals

• 16 articleJ. A.Juan A Fraire, S.Santiago Henn, G.Gregory Stock, R.Robin Ohs, H.Holger Hermanns, F.Felix Walter, L.Lynn van Broock, G.Gabriel Ruffini, F.Federico Machado, P.Pablo Serratti and J.Jose Relloso. Quantitative analysis of segmented satellite network architectures: A maritime surveillance case study.Computer Networks255February 2024, 110874HALDOI
• 17 articleA.Angelo Furno, A. F.André Felipe Zanella, R.Razvan Stanica and M.Marco Fiore. Spatial and Temporal Exploratory Factor Analysis of Urban Mobile Data Traffic.Data Science for Transportation64March 2024HALDOI
• 18 articleA.Aroosa Hameed, J.John Violos, N.Nina Santi, A.Aris Leivadeas and N.Nathalie Mitton. FeD-TST: Federated Temporal Sparse Transformers for QoS prediction in Dynamic IoT Networks.IEEE Transactions on Network and Service ManagementNovember 2024HALDOI
• 19 articleO.Oscar Ledesma, P.Paula Lamo, J. A.Juan A Fraire, M.María Ruiz and M. A.Miguel A Sánchez. Architectural Framework and Feasibility of Internet of Things-Driven Mars Exploration via Satellite Constellations.Electronics137March 2024, 1289HALDOI
• 20 articleR.Raydel Ortigueira, S.Samuel Montejo-Sánchez, S.Santiago Henn, J.Juan Fraire and S.Sandra Céspedes. Satellite Visibility Prediction for Constrained Devices in Direct-to-Satellite IoT Systems.IEEE Sensors Journal2416August 2024, 26630-26644HALDOI
• 21 articleW.Weixuan Xiao, N.Nancy El Rachkidy and A.Alexandre Guitton. Improving collision resolution of superposed LoRa signals using a Slot-Free Decoding Scheme.Ad Hoc Networks157April 2024, 103442HALDOI

International peer-reviewed conferences

• 22 inproceedingsA.Ahmed Boubrima, Z.Zhambyl Shaikhanov and E.Edward Knightly. Toward Accurate Environmental Mapping using Balloon-based UAVs.IEEE Consumer Communications & Networking ConferenceIEEE CCNC 2024IEEE CCNC 2024Las vegas, NV (US), United StatesJanuary 2024, 1-8HAL
• 23 inproceedingsR. L.Ronny L Bull, R. M.Rachel M Dudukovich, J. A.Juan A Fraire, N.Nadia Kortas, R.Robert Kassouf-Short, A.Aaron Smith and E.Ethan Schweinsberg. Network Emulation Testbed Capabilities for Prototyping Space DTN Software and Protocols.IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)Vancouver, FranceIEEEMay 2024, 1-8HALDOI
• 24 inproceedingsG. O.Gwladys Ornella Djuikom Foka, S.Solohaja Rabenjamina, R.Razvan Stanica and D.Diala Naboulsi. Human Presence Hotspot Extraction: A Mobile Network Data-Oriented Analysis.NetMob 2024 - International Conference on the Analysis of Mobile Phone DatasetsWashinghton DC, United StatesOctober 2024HAL
• 25 inproceedingsS. I.Sebastián I Montoya, D.Diego Maldonado, J. A.Juan A Fraire and S.Sandra Céspedes. On the Role of Delay Tolerant Networks and Contact Graph Routing in Direct-to-Satellite IoT.2024 IEEE 10th International Conference on Space Mission Challenges for Information Technology (SMC-IT)Mountain View, FranceIEEEJuly 2024, 151-160HALDOI
• 26 inproceedingsH. B.Hannaneh B Pasandi, J. A.Juan A Fraire, S.Sylvia Ratnasamy and H.Herve Rivano. A Survey on Direct-to-Device Satellite Communications: Advances, Challenges, and Prospects.LEO-NET '24: Proceedings of the 2nd International Workshop on LEO Networking and CommunicationWashington DC USA, United StatesACMNovember 2024, 7-12HALDOI
• 27 inproceedingsG. S.Geymerson S Ramos, R.Razvan Stanica, R. G.Rian G.S. Pinheiro and A. L.Andre L.L. Aquino. Optimizing Vehicular Users Association in Urban Mobile Networks.WCNC 2024 - IEEE Wireless Communications and Networking ConferenceDubai, United Arab EmiratesIEEEJuly 2024, 1-6HALDOI
• 28 inproceedingsC.Camilo Rojas, J. A.Juan A Fraire, F.Fabio Patrone and M.Mario Marchese. Advanced Constellation Emulation and Synthetic Datasets Generation for Non-Terrestrial Networks.2024 IEEE International Mediterranean Conference on Communications and Networking (MeditCom)Madrid, FranceIEEEJuly 2024, 37-43HALDOI
• 29 inproceedingsS.Sekinat Yahya and R.Razvan Stanica. Assessing the Energy Impact of Cell Switch Off at an Urban Scale.STWiMob 2024 - 17th International Workshop on Selected Topics in Wireless and Mobile ComputingParis, FranceOctober 2024HAL

National peer-reviewed Conferences

• 30 inproceedingsY.Yann Busnel and H.Hervé Rivano. FTM-Broadcast : Détermination efficace de coordonnées sur un réseau à grande échelle.CoRes 2024: 9èmes Rencontres Francophones sur la Conception de Protocoles, l'Évaluation de Performance et l'Expérimentation des Réseaux de CommunicationCoRes 2024: 9èmes Rencontres Francophones sur la Conception de Protocoles, l'Évaluation de Performance et l'Expérimentation des Réseaux de CommunicationSaint-Briac-sur-Mer, FranceMay 2024HAL
• 31 inproceedings G. H.Gwendoline Hochet Derévianckine, A.Alexandre Guitton, O.Oana Iova, B.Baozhu Ning and F.Fabrice Valois. Mais qui se cache ici ? CoRes 2024: 9èmes Rencontres Francophones sur la Conception de Protocoles, l'Évaluation de Performance et l'Expérimentation des Réseaux de Communication CoRes 2024 - 9èmes Rencontres Francophones sur la Conception de Protocoles, l'Évaluation de Performance et l'Expérimentation des Réseaux de Communication Saint-Briac-sur-Mer, France May 2024 HAL
• 32 inproceedings Z.Zhiyi Zhang, R.Razvan Stanica and F.Fabrice Valois. De l'intérêt d'utiliser des stations de base mobiles pour les premiers secours ! CoRes 2024: 9èmes Rencontres Francophones sur la Conception de Protocoles, l'Évaluation de Performance et l'Expérimentation des Réseaux de Communication CoRes 2024: 9èmes Rencontres Francophones sur la Conception de Protocoles, l'Évaluation de Performance et l'Expérimentation des Réseaux de Communication Saint-Briac-sur-Mer, France May 2024 HAL

Conferences without proceedings

• 33 inproceedingsA. Y.Alexander Y Choquenaira-Florez. On the role of ML in Satellite IoT: A survey of techniques, challenges and future directions.NTN Days 2024Grenoble, FranceOctober 2024HAL
• 34 inproceedingsF.Florent Dobler, M. R.Marcos Rojas Mardones, O.Olivier Alphand, D.Didier Donsez, J. A.Juan A. Fraire, M.Martin Heusse and O.Oana Iova. In-vivo experiments on LR-FHSS modulation.Journées LPWAN 2024Pau (FRA), FranceJuly 2024HAL
• 35 inproceedingsC.Carlos Fernandez Hernandez, O.Oana Iova and F.Fabrice Valois. Downlink Scheduling in LoRaWAN: ChirpStack vs The Things Stack.IEEE Latin-American Conference on CommunicationsMedellin, ColombiaNovember 2024HALback to text
• 36 inproceedingsA.Alice Le Bihan, J. A.Juan Andrés A Fraire and F.Felix Flentge. Enhanced Custody Transfer and Status Reporting for Delay Tolerant Space Networks.NTN Days 2024Grenoble, FranceOctober 2024HAL
• 37 inproceedingsA.Andreas Schmidt, H.Holger Hermanns, J. A.Juan Andrés A Fraire, R.Robin Ohs, G.Gregory Stock and S. M.Santiago M Henn. Be The (Route) Change.NTN Days 2024Grenoble, FranceOctober 2024HAL

Scientific book chapters

• 38 inbookC. E.Carlos E Budde, P.Pedro D’argenio, J. A.Juan Andrés A Fraire, A.Arnd Hartmanns and Z.Zhen Zhang. Modest Models and Tools for Real Stochastic Timed Systems.15261Principles of Verification: Cycling the Probabilistic LandscapeLecture Notes in Computer ScienceSpringer Nature SwitzerlandNovember 2024, 115-142HALDOI

Edition (books, proceedings, special issue of a journal)

• 39 proceedingsProceedings of the 3rd International Conference on 6G Networking (6GNet 2024).2024 3rd International Conference on 6G Networking (6GNet)IEEEDecember 2024HALDOI

Doctoral dissertations and habilitation theses

• 40 thesisW.Walid Bechkit. Contributions to Wireless Sensor Networks for Air Quality Monitoring.INSA LyonMay 2024HAL
• 41 thesisG. H.Gwendoline Hochet Derévianckine. Feasibility and Performance of a LoRa 2.4 GHz Network.Insa LyonDecember 2024HAL
• 42 thesisL.Lucas Magnana. Learning algorithms for urban cycling : Implicit models and dynamic infrastructure.INSA LyonFebruary 2024HAL
• 43 thesisC.Camille Moriot. Methodology for socio-organizational characterization of IP addresses applied to security.INSA de LyonSeptember 2024HAL

Reports & preprints

• 44 miscG. H.Gwendoline Hochet Derévianckine, A.Alexandre Guitton, O.Oana Iova, B.Baozhu Ning and F.Fabrice Valois. Hate or Love in the 2.4 GHz ISM band: The Story of LoRa® and IEEE 802.11g.December 2024HAL
• 45 miscS. M.Santiago M Henn, J. A.Juan Andrés A Fraire, N.Nicola Accettura, S.Sandra Céspedes and H.Holger Hermanns. Multi-Gateway LoRaWAN Throughput Modeling in Direct-to-Satellite IoT Constellations.October 2024HAL
• 46 miscI.Ichrak Mokhtari, W.Walid Bechkit, M. S.Mohamed Sami Assenine and H.Herve Rivano. Navigating the Smog: A Cooperative Multi-Agent RL for Accurate Air Pollution Mapping through Data Assimilation.July 2024HALDOI