2023Activity reportProject-TeamAGORA

7.1.1 PrivaMovApp

• Keyword:
  Crowd-sensing
• Functional Description:
  Agora is leading the development of an Android application for user data collection purposes. The application is based on the Funf framework.
• Contact:
  Razvan Stanica
• Participants:
  Stéphane D'Alu, Hervé Rivano, Razvan Stanica, Solohaja Rabenjamina

7.1.2 urpolsens

• Name:
  UrPolSens Platform
• Keywords:
  Wireless Sensor Networks, Air Quality
• Functional Description:
  A micro-controller is integrated into a lab-designed printed circuit which includes among others: a high precision ADC, a micro-SD card reader and a radio communication module. The designed nodes measure the nitrogen dioxide (NO2) pollutant in addition to temperature and humidity, and transmit data using LoRa to a gateway, which is connected to our servers using a 4G connection. The sensors are also equipped with solar panels in order to extend their lifetime when their batteries are drained. Our platform has been operational in the downtown of the city of Lyon with 12 sensor nodes deployed in the Garibaldi street from mid-July to mid-October 2018. It has then been improved and generalized to match the need of the collaboration with Total LQA lab. It is now a versatile multi-sensors platform able to run autonomously on solar energy for months.
• Contact:
  Walid Bechkit
• Participants:
  Walid Bechkit, Hervé Rivano
• Partner:
  Intelligence des Mondes Urbains

7.1.3 3M’Air

• Name:
  3M’Air Platform
• Keywords:
  Wireless Sensor Networks, Air Quality
• Functional Description:
  We have built our own nodes equipped with multiple sensors measuring Nitrogen-Dioxide (NO2), Particulate Matter (PM1, PM2.5, PM10), temperature and humidity. They are battery-powered and equipped with a GPS module to have the position of the measurements. Data are stored on a micro SD card and at the same time sent over LoRa to a server we have developed that is responsible to store these data for future analysis. A web platform has also been developed to display the collected concentration measurements in real time. This developed solution is used in several participatory planned measurement campaigns in Lyon city.
• Contact:
  Walid Bechkit
• Participants:
  Walid Bechkit, Hervé Rivano
• Partner:
  Intelligence des Mondes Urbains

7.1.4 eSmartCity

• Name:
  eSmartCity Smart Lighting platform
• Keywords:
  Lighting, Sensors
• Functional Description:
  The objective is to analyze the pedestrian mobility on a street and to evaluate the opportunity to deploy a Smart Lighting solution. Mobility is monitored using PIR sensors and correlated with light, environment and noise sensor measurements. We are discussing with a company the opportunity to adapt our sensors to their own public lighting products.
• Contact:
  Oana Iova
• Participants:
  Oana Iova, Hervé Rivano

7.1.5 Dense LoRaSim

• Name:
  Extension to support dense LPWAN in LoRaSim
• Keyword:
  LoRaWAN
• 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

7.1.6 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

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 plateform 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).

UTOPIA 

It is a platform of LoRaWAN-based low-cost sensor networks for industrial pollution monitoring sensor nodes that we designed and implemented for two projects. Sensor nodes that we designed and implemented have been used in two operational deployments: the first one was carried out on onshore industrial site for the assessment of pollutant emissions while the second one was operated on offshore site for monitoring occupational exposure to pollutants.

UrPolSens Platform 

We designed from scratch an energy efficient air pollution sensor network using Atmega micro-controllers and electrochemical air pollution probes. The micro-controller is integrated into a lab-designed printed circuit which includes among others: a high precision ADC, a micro-SD card reader and a radio communication module. The designed nodes measure the nitrogen dioxide (NO2) pollutant in addition to temperature and humidity and transmit data using LoRa to a gateway, which is connected to our servers using a 4G connection. The sensors are also equipped with solar panels in order to extend their lifetime when their batteries are drained. Our platform has been operational in the downtown of the Lyon city with 12 sensor nodes deployed in the Garibaldi street from mid-July to Mid-October 2018.

3M'air sensor platform 

We developed the 3M'Air sensor platform to be used in participatory sensing of temperature and air quality. We have built our own nodes equipped with multiple sensors measuring Nitrogen-Dioxide (NO2), Particulate Matter (PM1, PM2.5, PM10), temperature and humidity. They are battery-powered and equipped with a GPS module to have the position of the measurements. Data are stored on a micro SD card and at the same time sent over LoRa to a server we have developed that is responsible to store these data for future analyses. A web platform has also been developed to display the collected concentration measurements in real time. This developed solution is used in several participatory planned measurement campaigns in Lyon city.

The AgoraLTEplateform (ALP) 

The AgoraLTEplateform is leveraging the opensource srsLTE software suite and Software Defined Radio (SDR) to perform experimental research about autonomous and flexible cellular networks. This platform emulates an entire cellular network thanks to three software components of srsLTE. The cellular network is composed of three main elements: the core network (srsEPC), the radio access network (srsENB) ans the user equipment (srsUE). Those elements can be run on several remote machines and operate an LTE connection by the means of SDR elements: USRP-2901 from National Instrument in our case. We also have at our disposal custom sim cards usable by any off-the-shelf smartphone that permit them to access the experimental network. This platform being run by a regularly updated open source code allows us to modify its structure, tune, add or remove network parameters and run scientific experiments that are yet to few in the literature. This testbed is issued to investigate new user association mechanisms considering quality of service requirements, or emergency situations.

Cooperative Deep Reinforcement Learning for Dynamic Pollution Plume Monitoring using a Drone Fleet

Monitoring pollution plumes is a key issue, given the harmful effects they cause. The dynamic of these plumes, which may be important due to meteorological conditions, makes their study difficult. Real-time monitoring in order to obtain an accurate mapping of the pollution dispersion is helpful and valuable to mitigate risks. We consider a fleet of cooperative drones carrying pollution sensors and operating in order to assess a pollution plume 17. The latter is assumed to follow a Gaussian Process (GP) with varying parameters. For this use case, we propose an efficient approach to characterize spatially and temporarily the plume while optimizing the path planning of drones. In our approach, drones are guided by a Deep Reinforcement Learning (DRL) model called Categorical Deep Q-Network (Categorical DQN) to maximize the plume coverage while considering budget constraints. Specifically, we develop a scalable Independent Q-Learning (IQL) scheme that shares team rewards based on each drone's deployment relevance and therefore ensures cooperation. We evaluate the performance of the plume parameter estimation as well as the maps generated by the GP regression. By testing our framework on several plume scenarios, we show that it offers good results in terms of both estimation quality and run-time efficiency.

Opportunities and challenges of LoRa 2.4 GHz

Internet of Things (IoT) technologies are increasingly used in our daily life. Among these technologies, LoRa is widely used for low power IoT data collection in wide areas. LoRa typically operates in sub-GHz bands which are region-specific, and thus has limited worldwide applications. The version of LoRa developed for the 2.4 GHz ISM band has spurred recent interest in the scientific community, as it enables the use of worldwide frequency channels. However, it requires the coexistence with numerous concurrent technologies within this 2.4 GHz band, and an evolution of the MAC and networking protocols for utilizing LoRaWAN connectivity. In 19, we make the first experimental comparison between LoRa sub-GHz and LoRa 2.4 GHz in both indoor and outdoor scenarios. We show that LoRa 2.4 GHz can have a communication range of more than 2 km outdoor, and it can achieve a packet delivery rate of at least 0.98 for a distance of up to 39 meters indoor with the presence of obstacles. We also make an extensive discussion on the researches challenges that need to be addressed in order to fully take advantage of this new technology.

Polygon-based algorithms for N-satellite constellations coverage computing

Satellite Coverage Analysis is a fundamental performance assessment element in remote sensing and communications services projects. Coverage is a key parameter in the constellation operation and design for missions relying on several satellites. Since coverage areas over the surface of the Earth change with time, intersecting and drifting apart, the dynamics of every satellite influence the constellation's behavior as a whole. For this reason, every configuration change, be it in the number of satellites or their relative positions, heavily impacts the cost/performance of the mission. In 20, we present a constellation-to-ground coverage analysis model that enables the rapid evaluation of areas on the surface of the Earth. The method leverages geodetic projections and an oblate Earth model and uses dynamic transformation and anti-transformation techniques combined with polygon Boolean operations. Timestamped datasets are obtained to account for the dynamics of the scenario, which can be exploited in statistical coverage analysis of the constellation. Our empirical evaluations show that this approach is superior in accuracy and computation effort compared to traditional net-point techniques. While net-point approaches are at the core of state-of-the-art commercial software, they are approximate. We show that, for finer grid granularity, the netpoint schemes converge to our polygon-based results.

Everyone can slice LoRaWAN

Long-Range Wide Area Networks (LoRaWAN) enable low-power data collection over long distances, and they are thus widely used for Internet of Things applications, despite their limitations to meet some traffic requirements (e.g., reliability). To achieve the quality of service required by the applications, service differentiation is a promising approach which can be provided by network slicing. In 27, we show that related works are either incompatible with the LoRaWAN specifications, or do not isolate traffic, or assume an a priori known and stable traffic. In this paper, we propose a lightweight approach to achieve slicing in LoRaWAN, compatible with the LoRaWAN specifications. Our approach allows to isolate traffic, to protect confirmed traffic, and to deal with unsolicited traffic.

Heterogeneous IoT/LTE ProSe virtual infrastructure for disaster situations

Natural disasters of any kind can have catastrophic consequences for properties, infrastructure, and human lives. During large-scale calamities, two common problems are faced: (i) the partial or even complete destruction of communications infrastructure, and (ii) the difficulty of collecting accurate information on the disaster area and trapped victims. These two problems prevent a quick and accurate assessment of damage, leading to inefficient rescue operations and putting the lives of rescuers and victims in great danger. The LTE Proximity Services (ProSe) and the Internet of Things (IoT) are promising technologies that can offer an efficient solution to the aforementioned problems in the form of a rapidly established emergency network for post-disaster management. In this 15, we propose a solution for the establishment of an efficient emergency communications network for post-disaster situations based on the LTE Device-to-Device ProSe (D2D ProSe) technology and IoT devices. It facilitates fast and efficient service discovery that allows querying heterogeneous IoT devices such as health sensors, wireless cameras, smartwatches, or any other relevant devices or sensors. The goal is to allow rescuers to have access to information produced by various things available during the rescue operation. We take advantage of LTE ProSe to create a distributed D2D broadcast backbone that enables efficient and reliable message dissemination while reducing energy consumption and achieving high coverage. We then add a multipath forwarding mechanism, in which each service type of IoT device is ensured an optimal path for its traffic. Unlike previous works, we fully implemented our solution in the NS3 simulator and relied on realistic models (wireless channels, energy, and mobility) to evaluate its performance compared to previous solutions, which we also implemented on NS3. The obtained results show that our solution achieves significant improvement compared to those proposed in the literature. The entire code used in this project is freely available to the community through GitHub.

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 25 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. This motivates further research in multi-PHY adaptation for KPIs specific to industrial robotics.

Routing in future space‐terrestrial integrated networks with SATNET‐OSPF

Summary Connectivity in satellite networks is governed by the spacecraft nodes' orbital dynamics together with the planet's continuous rotation where ground nodes are located. The resulting time‐dynamic but predictable topology demands the design of specific distributed routing schemes. However, terrestrial Internet routing schemes' maturity, proven scalability, and efficiency shall be leveraged whenever possible to facilitate space‐terrestrial integration while reducing risk and costs. In line with this reflection, we introduce SATNET‐OSPF: a backward‐compatible satellite extension for the widely used Open Shortest Path First routing protocol 26. The key features of SATNET‐OSPF are (a) accurate routing interface mapping to inter‐satellite links and ground‐to‐satellite links, (b) accelerated link‐up/link‐down event detection adapted to space‐specific wireless technologies, (c) proactive routing and forwarding mechanism to take advantage of predicted link‐down events, and (d) low memory footprint topology model to efficiently propagate the forthcoming space connectivity events via constrained telecommand links. Leveraging existing IPv6 and OSPFv3 open‐source stacks, we implemented SATNET‐OSPF in an actual space router comprising a space‐grade SPARC V8 CPU and a radiation‐hardened FPGA. Furthermore, we present the details of an emulation test bench supporting various configurations with COTS terrestrial OSPF routers that enabled a realistic performance evaluation of the SATNET‐OSPF. Results show that SATNET‐OSPF reduced OSPFv3 routing protocol overhead by up to 31%; shortened the link event detection delay by four orders of magnitude; decreased the routing outage by a factor of 22; and ensured flooding control message generation and forwarding times, as well as routing computing time, satisfy the original requirements (192, 37, and 17 ms, respectively).

FTM-Broadcast: efficient network-wide ranging

Indoor geolocation has witnessed a significant advancement through the refinement of the 802.11 FTM (Fine Timing Measurement) protocol. Accurate indoor geolocation has numerous applications in areas such as asset tracking, indoor navigation, and location-based services. The standard 802.11 FTM protocol enables accurate indoor positioning by measuring the time-of-flight between a mobile device and multiple access points (APs). It can be generalized to device-to-device ranging. However, the conventional implementation of FTM suffers from increased complexity as the number of devices grows, limiting its scalability. FTM indeed involves a point-to-point exchange of messages between each pair of devices, leading to a quadratic increase in the number of messages as the number of neighboring devices increases. In 30, a breakthrough method is proposed to enhance the FTM protocol by leveraging broadcast communication, resulting in a substantial reduction in message complexity from quadratic to linear. By taking into account broadcast in the protocol, our approach eliminates the need for multiple individual exchanges and devises a mechanism where a single message from the mobile device is broadcasted to all neighbors simultaneously. Each message exchanged will then be useful for computing every pairwise time-of-flight, by piggybacking all timestamps, making the protocol more efficient and scalable. We conducted extensive simulated experiments to evaluate the performance of the enhanced FTM protocol. The results demonstrated the effectiveness of the proposed method, showcasing a substantial reduction in computational overhead compared to the conventional FTM implementation.

Recovering Headerless Frames in LR-FHSS

Long-Range Frequency Hopping Spread Spectrum (LR-FHSS) is a recent modulation designed for communications from low-power ground end-devices to Low-Earth Orbit (LEO) satellites. To decode a frame, an LR-FHSS gateway must receive at least one header replica and a large proportion of payload fragments. However, LR-FHSS headers will likely be lost when there are many concurrent transmissions. In 36, we motivate the header loss problem with an analytical model, propose a linear programming model to extract headerless frames and design a cost-effective sliding window heuristic. Simulation results show that our approach exhibits near-optimal headerless detection and extraction results while ensuring a low computational cost. The proposed method is, therefore, suitable for future LR-FHSS gateways located onboard resource-constrained LEO satellites.

Probabilistic and distributed traffic control in LPWANs

Low-power, low data transmission rates, and long-range wireless networks, also known as LPWANs, are intended to work best with equipment that uses few resources and can be used for many years thanks to their long battery life operation. This type of networks can handle traffic from nearly 1,000 nodes while maintaining a duty cycle of less than 1%. However, as the nodes become denser, the number of collisions increases and network traffic management becomes mandatory. To address this concern, we propose a Distributed and Probabilistic Traffic Control algorithm (DiPTC) 21 that allows nodes to change their traffic in response to the application requirements (e.g., acquiring K measurements over a period of time) while being agnostic to the number of nodes or the network topology. When this requirement is not achieved, the gateway sends a feedback message to all the nodes so that they may adapt their traffic. We compare the proposed solution to LoRaWAN and to a Centralized Optimal Traffic Control solution (COTraC), in simulation. Compared to LoRaWAN, our algorithm proved successful in achieving the objective while minimizing collisions and extending the network lifetime threefold.

Where Are The (Cellular) Data?

New generations of cellular networks are data oriented, targeting the integration of machine learning (ML) and artificial intelligence solutions. Data availability, required to train and compare ML-based networking solutions, is therefore becoming an important topic and a significant concern. Operators do collect data, but they rarely share it because of privacy concerns. In 16, we review the few publicly available cellular datasets, which created bursts of innovation with their release. The scarcity of such data is so acute that researchers are collecting network data using their own tools, developed in-house and covered by the second part of this survey.

Multi-slice privacy-aware traffic forecasting at RAN level: a scalable federated-learning approach

Next-generation mobile networks are expected to meet the requirements of a wide range of new vertical services. Hence, the network slicing concept has been introduced, in which Mobile Virtual Network Operators (MVNOs) are allowed to provide various types of services over the same physical infrastructure, owned by an Infrastructure Provider (InP). To cope with an ever-changing traffic demand, MVNOs seek to preallocate/reconfigure the resources at the base stations in an anticipatory manner, based on traffic demand predictions. Ideally, conducting per-slice traffic forecasting requires information that is likely to disclose MVNO confidential information (i.e., business strategy or private user data). To secure data ownership while conducting traffic forecasting, we propose the Federated Proximal Long Short-Term Memory (FPLSTM) framework, which allows MVNOs to train their local models with their private dataset at each base station; subsequently, an associated InP global model can be updated through the aggregation of the local models 24. The results obtained by training the models on a realworld dataset indicate that the forecasting performance of our proposed approach is as accurate as state-of-the-art centralized solutions, while improving data privacy. To enable scalability, we further propose the Information-based Clustering FPLSTM (IC-FPLSTM) and Random Clustering FPLSTM (RC-FPLSTM) frameworks, dealing with large-scale cellular networks. These solutions demonstrate computation and communication cost efficiency significantly above the state-of-the-art.

Toward deep digital contact tracing: opportunities and challenges

During the COVID-19 pandemic, digital contact tracing using mobile devices has been widely explored, with many proposals from academia and industry highlighting the benefits and challenges. Most approaches use Bluetooth low energy signals to learn and trace close contacts among users. However, tracing only these contacts can mask the risk of virus exposure in scenarios with low detection rates. To address this issue, we propose fostering users to exchange information beyond close contacts, particularly about prior “deep” contacts that may have transmitted the virus 18. This presents new opportunities for controlling the spread of the virus, but also poses challenges that require further investigation. We provide directions for addressing these challenges based on our recent work developing a technological solution using this approach.

On data selection for the energy efficiency of neural networks: Towards a new solution based on a dynamic selectivity ratio

In 28 we address the energy efficiency of neural networks training through data selection techniques. We first study the impact of a random data selection approach that renews the selected examples periodically during training. We find that random selection should be considered as a serious option as it allows high energy gains with small accuracy losses. Unexpectedly, it even outperforms a more elaborate approach in some cases. Our study of the random approach conducted us to observe that low selectivity ratios allow important energy savings, but also cause a significant accuracy decrease. To mitigate the effect of such ratios on the prediction quality, we propose to use a dynamic selectivity ratio with a decreasing schedule, that can be integrated to any selection approach. Our first results show that using such a schedule provides around 60% energy gains on the CIFAR-10 dataset with less than 1% accuracy decrease. It also improves the convergence when compared to a fixed ratio.

10.1.1 STIC/MATH/CLIMAT AmSud projects

10.2.1 Visits of international scientists

10.2.2 Visits to international teams

10.3.1 H2020 projects

• 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 (4years)
  • Coordinator: University of Twente, Netherlands
  • Other partners: Netherlands RWTH Aachen University, Germany Saarland University, 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.
• Program: H2020-ICT-2018-2020
  • Project acronym: BUGWRIGHT2
  • Project title: Autonomous Robotic Inspectionand Maintenance on Ship Hulls and Storage Tanks
  • Duration: 01/2020-03/2025
  • Coordinator: Georgia Tech Lorraine / UMI 2958 GT - 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 adapt- able 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 crawlers 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.

10.3.2 Other european programs/initiatives

• Program: CHIST-ERA 20202
  • 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
  • Otherpartners: 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.

10.4.1 GDR CNRS RSD

• Ongoing participation (since 2006)

  Communication networks, working groups of GDR ASR/RSD, CNRS. Oana Iova is in charge of the mentorship actions (e.g., seminars) for the GDR RSD. 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 chair of the Networking axis of the GDR RSD. All the members of Agora are regular participants to the GDR RSD.

11.1.1 Scientific events: organisation

11.1.2 Scientific events: selection

11.1.3 Journal

11.1.4 Invited talks

• Anais Boumendil and Walid Bechkit gave a pitch on the energy effeciency of deep neural networks as part of the Digital weeks at INSA-Lyon, Lyon, April 2023.
• Walid Bechkit gave a seminar on LoRa-based WSNs for air quality moinitring at Schneider Electric, Grenoble, June 2023.
• Walid Bechkit gave an invited talk as part of the INSA-Lyon scientific day on environment, Lyon, October 2023.
• Juan A. Fraire was invited to give a talk about Routing in the Interplanetary Internet of Things, IEEE 9th World Forum on Internet of Things, Portugal, October 2023
• Juan A. Fraire was invited to give a talk about Delay-Tolerant Networking Modeling and Experimentation, IEEE Cognitive Communications for Aerospace Applications (CCAA), July 2023.
• Juan A. Fraire was invited to give a talk about Interplanetary Internet of Things: Protocols, Routing, and Simulation, i2Cat Workshop, Universidad Politecnica de Catalunya, Spain, October 2023.
• Oana Iova gave an invited talk about Low Power Wide Area Networks Experimental Results, National Institute of Informatics, Japan, April 2023.

11.1.5 Leadership within the scientific community

• Oana Iova is in charge of the mentorship actions (e.g., seminars) for the GDR RSD.
• Razvan Stanica is member of the scientific council of the GDR RSD.
• Fabrice Valois is chair of the scientific council of the Labex IMU.
• Fabrice Valois is member of the steering committee of the GDR RSD.
• Fabrice Valois is chair of the Networking axis of the GDR RSD.
• Fabrice Valois is member of the COURSE, in charge to identify and to define use cases, applications, and scenarios for the national testbed SLICE-FR (networking and cloud).

11.1.6 Scientific expertise

• Walid Bechkit is member of "Club des experts" of the "Conseil Économique, Social et Environ- nemental Régional - CESER - ATMO-AURA".
• Walid Bechkit was expert for ANR project, 2023.
• Walid Bechkit was expert for one application for CIFRE grant, 2023.
• Oana Iova was member of the following recruitment committee:
  • Associate professor position, INSA Hauts de France.
  • Associate professor position, INSA Lyon.
  • Associate professor position, Université Toulouse Jean Jaurès.
  • Associate professor position, INP Toulouse.
• Fabrice Valois was member of the following recruitment committee:
  • Associate professor position, Computer Science / web development, LIMOS, Université Clermont Auvergne.
  • Associate professor position, Computer Science / Networking / HPC, I-Cube, IUT Robert Schumann, Université de Strasbourg.
  • Associate professor position, Computer Science / Adaptivity and programmability of networks, IRIT, Université Toulouse 3.

11.2.1 Teaching

11.2.2 Supervision

• Masters
  • xxx
• PhD Thesis (defended in 2023)
  • Ichrak Mokhtari , Spatio-temporal data analysis for dynamic phenomenon monitoring using mobile sensors, INSA Lyon, June 2023
  • Mihai Popescu, Connectivity constrained mobility in fleets of robots, INSA Lyon, July 2023.
  • Solohaja Rabenjamina , Gestion de la Mobilité Urbaine et dans le Réseau Mobile à partir de Données de Téléphonie, INSA Lyon, September 2023.
• PhD Thesis (started in 2023)
  • 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.
• PhD Thesis (on going)
  • 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).
  • Gwladys Djuikom, Mobility analysis using cellular data, since 10/2021. Advisors: Diala Naboulsi (ETS Montréal, Québec, Canada), Razvan Stanica.
  • Mohamed El Emary, Taskoff loading in airborne-assisted networks, since 07/2021. Advisors: Diala Naboulsi (ETS Montréal, Québec, Canada), Razvan Stanica.
  • Gwendoline Hochet Derevianckine,Faisabilité et performances d’un réseau LoRaWAN dans la bande ISM 2.4GHz, since 04/2021. Advisors: Alexandre Guitton, Oana Iova, Baozhu Ning (Semtech), Fabrice Valois.
  • Kawtar Lasri, Data collection and distributed spatial coordination in LPWAN networks, since 01/2019. Advisors: Oana Iova, Yann Ben Maissa (INPT Rabat, Morocco), Fabrice Valois.
  • Lucas Magnana, De la ville intelligente à la ville prédictive, application aux modes de transport actifs, since 10/2020. Advisors: Nicolas Chiabaut (LICIT, ENTPE / IFSTTAR), Hervé Rivano.
  • Diego Maldonado Munoz, Adaptations, Optimizations, and Learning Approaches for Direct- to-Satellite Internet of Things, since 12/2022. Adivsors: Juan A. Fraire, Hervé Rivano.
  • Camille Moriot, DDos Attacks and their impacts on the Internet Architecture, since 09/2020. Advisors: François Lesueur (IRISA / UBS) Nicolas Stouls (CITI), Fabrice Valois.
  • Hnin Pann Phyu, End-to-end mobile network slicing, since 10/2020.Advisors: Diala Naboulsi (ETS Montréal, Québec Canada), Razvan Stanica.
  • 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.

11.2.3 Juries

• Oana Iova was an examiner of the following PhD defense :
  • Weixuan Xiao, Techniques de décodage pour annuler les collisions dans LoRa Université Clermont Auvergne, June 2023.
  • Alessandro Aimi, Algorithms for reliability insurance and traffic differentiation in low power internet of things communication networks, CNAM, September 2023.
  • Farzad Veisi, Software Defined Industrial Internet of Things, University of Strasbourg, ICube, November 2023.
  • Joakim Eriksson, Scalable and Interoperable Low-Power Internet of Things Networks, Uppsala University, Sweden, December 2023.

• Hervé Rivano was reviewer of the following HDR:
  • Angelo Furno, Approches fondées sur les données pour améliorer la résilience des réseaux de transport à grande échelle, Université Gustave Eiffel, November 2023.

• Hervé Rivano was an president of the jury of the following PhD defense :
  • Mahdi Sharara, Resource Allocation in Future Radio Access Networks, Université Paris Saclay, March 2023.

• Hervé Rivano was an reviewer of the following PhD defense :
  • Guillaume Beduneau, Prédiction de comportement des algorithmes coopératifs dans les réseaux véhiculaires, Université de Technologie de Compiègne, March 2023.
  • Igor Dias da Silva, Optimisation du déploiement et de la coordination de drones pour les applications d'exploration et de surveillance, Université Côte d'Azur, September 2023.
  • Firmin Kateu, Des solutions basées sur les smarphones pour des soins de santé accessibles et en continus, Toulouse INP, November 2023.
  • Nina Santi, Prédiction des besoins pour la gestion de serveurs mobiles en périphérie, Université de Lille, December 2023.
  • Mohamed Idir, Analyse et développement de modèles statistiques pour l'estimation et la prédiction spatiale et temporelle de la pollution atmosphérique à partir de données issues de capteurs mobiles, Université Paris Saclay, December 2023.

• Razvan Stanica was a reviewer of the following PhD defense :
  • Chaima Zoghlami, Amélioration des systèmes de communication V2X pour la perception coopérative : sécurité des usagers de la route, Toulouse 3, October 2023.

• Razvan Stanica was an examiner of the following PhD defense :
  • Razanne Abu-Aisheh, Context-Aware Information Gathering and Processing Towards Supporting Autonomous Systems in Industry 4.0 Scenarios, Sorbonne Université, February 2023.
  • Fabien Meslet-Millet, Apprentissage profond pour le trafic réseau : classification, génération et compression, Toulouse INP, November 2023.

• Fabrice Valois was a reviewer of the following HDR:
  • Nancy El Rachkidy, Étude et amélioration des performances d’un réseau LoRa, LIMOS, Université Clermont Auvergne, November 2023.

• Fabrice Valois was a reviewer of the following PhD defense :
  • Mishra Debashisha, Exploiting the synergies of unmanned aerial vehicles (UAVs) and 5G network, LORIA, Université de Lorraine, June 2023.

• Fabrice Valois was an examiner of the following PhD defense :
  • Lucas Bréhon-Grataloup, Architectures de communication pour les véhicules autonomes connectés, IRIT, Université Toulouse 3, November 2023.
  • Arnol Lemogue, Réduction de l’impact du paradigme REST sur le DNS en utilisant des Technologies pour l’Internet des Objets, IRISA, IMT Atlantique, December 2023.

11.3.1 Internal or external Inria responsibilities

• Oana Iova is in charge of Sustainable and socially responsible development (DDRS) for Agora.
• Hervé Rivano is the best ever REP.

11.3.2 Articles and contents

• Alexandre Guitton is co-author of this popularization article about collision in LoRa network: "Signaux radio superposés : problème et solution", in La minute recherche, W. Xiao, N. El Rachkidy, A. Guitton, Université Clermont Auvergne, March 2023.

11.3.3 Education

• Hervé Rivano was invited by the French ambassy in Luxembourg for a discussion with high-school students, a visit of a smart city project, a popularization keynote, and a discussion diner with the Ambassador, Luxembourg, December 2023.
• Hervé Rivano was invited for a talk at the doctoral popularization seminar MOMI, Sophia Antipolis, April 2023.

11.3.4 Interventions

• Fabrice Valois gave a talk about Une histoire des communications, Exposition Brickus Maximus, Musée Lugdunum, Lyon, November 2023.
• Fabrice Valois gave a talk about Une vision globale des communications, Médiation Campus du Numérique, Inria / INSA Lyon, Lyon, December 2023.

International journals

• 15 articleS.Sami Abdellatif, O.Okba Tibermacine, W.Walid Bechkit and A.Abdelmalik Bachir. Heterogeneous IoT/LTE ProSe virtual infrastructure for disaster situations.Journal of Network and Computer Applications (JNCA)213April 2023, 103602HALDOIback to text
• 16 article M.Maryam Amini, R.Razvan Stanica and C.Catherine Rosenberg. Where Are The (Cellular) Data? ACM Computing Surveys July 2023 HAL DOI back to text
• 17 articleM. S.Mohamed Sami Assenine, W.Walid Bechkit, I.Ichrak Mokhtari, H.Hervé Rivano and K.Karima Benatchba. Cooperative Deep Reinforcement Learning for Dynamic Pollution Plume Monitoring using a Drone Fleet.IEEE Internet of Things JournalOctober 2023, 1-14HALDOIback to text
• 18 articleR.Renato Cherini, R.Ramiro Detke, J.Juan Fraire, P. G.Pablo G Madoery and J. M.Jorge M Finochietto. Toward Deep Digital Contact Tracing: Opportunities and Challenges.IEEE Pervasive Computing2023, 1-11HALDOIback to text
• 19 articleG. H.Gwendoline Hochet Derévianckine, A.Alexandre Guitton, O.Oana Iova, B.Baozhu Ning and F.Fabrice Valois. Opportunities and Challenges of LoRa 2.4 GHz.IEEE Communications Magazine2023HALDOIback to text
• 20 articleS. M.Santiago M Henn, J. A.Juan A Fraire and H.Holger Hermanns. Polygon-Based Algorithms for N -Satellite Constellations Coverage Computing.IEEE Transactions on Aerospace and Electronic Systems2023, 1-17HALDOIback to text
• 21 articleK.Kawtar Lasri, Y.Yann Ben Maissa, L.Loubna Echabbi, O.Oana Iova and F.Fabrice Valois. Probabilistic and distributed traffic control in LPWANs.Ad Hoc Networks143April 2023HALDOIback to text
• 22 articleD.Douglas Moura, G.Geymerson Ramos, A.Andre Aquino and A.Antonio Loureiro. A Centrality Approach to Select Offloading Data Aggregation Points in Vehicular Sensor Networks.IEEE Transactions on Intelligent Transportation Systems2411August 2023, 11639 - 11653HALDOI
• 23 articleH. P.Hnin Pann Phyu, D.Diala Naboulsi and R.Razvan Stanica. Machine Learning in Network Slicing - A Survey.IEEE Access11April 2023, 39123-39153HALDOI
• 24 articleH. P.Hnin Pann Phyu, R.Razvan Stanica and D.Diala Naboulsi. Multi-Slice Privacy-Aware Traffic Forecasting at RAN Level: A Scalable Federated-Learning Approach.IEEE Transactions on Network and Service ManagementApril 2023HALDOIback to text
• 25 articleM.Mina Rady, O.Oana Iova, H.Hervé Rivano, A.Angeliki Deligianni and L.Leonidas Drikos. How does Wi-Fi 6 fare? An industrial outdoor robotic scenario.Ad Hoc NetworksJanuary 2024, 103418HALDOIback to text
• 26 articleH.Hongcheng Yan, L.Liang Qiao, W.Wei Wu, J. A.Juan A Fraire, D.Dong Zhou, L.Luming Li and Y.Yong Xu. Routing in future space‐terrestrial integrated networks with SATNET‐OSPF.International Journal of Satellite Communications and NetworkingAugust 2023HALDOIback to text

International peer-reviewed conferences

• 27 inproceedingsT.Thibaut Bellanger, A.Alexandre Guitton, R.Razvan Stanica and F.Fabrice Valois. Everyone can slice LoRaWAN.IEEE International Conference on Wireless and Mobile Computing, Networking and CommunicationsMontréal, CanadaJune 2023HALback to text
• 28 inproceedingsA.Anais Boumendil, W.Walid Bechkit and K.Karima Benatchba. On data selection for the energy efficiency of neural networks: Towards a new solution based on a dynamic selectivity ratio.ICTAI 2023 - IEEE 35th International Conference on Tools with Artificial IntelligenceAtlanta (GA), United StatesNovember 2023HALDOIback to text
• 29 inproceedings A.Anais Boumendil, W.Walid Bechkit, P.-E.Pierre-Edouard Portier, F.Frédéric Le Mouël and M.Malcolm Egan. Grow, prune or select data: which technique allows the most energy-efficient neural network training? 2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI) Atlanta (GA), United States November 2023 HAL DOI
• 30 inproceedingsY.Yann Busnel and H.Hervé Rivano. FTM-Broadcast: Efficient Network-wide Ranging.13th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2023)IPIN 2023: 13th International Conference on Indoor Positioning and Indoor Navigation13th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2023)Nuremberg, GermanyIEEE; IEEESeptember 2023, 1-6HALDOIback to text
• 31 inproceedingsJ.-T.Jen-Tse Chen, M.Megumi Kaneko and A.Alexandre Guitton. An Auction-based Assignment Method for LoRa Multi-Gateway Networks.IEEE International Conference on CommunicationsRome, ItalyMay 2023HAL
• 32 inproceedingsG. O.Gwladys Ornella Djuikom Foka, R.Razvan Stanica and D.Diala Naboulsi. Handover Forecasting in Cellular Networks: A Spatio-temporal Graph Neural Network Approach.NoF 2023 - 14th International Conference on Network of the FutureIzmir, TurkeyOctober 2023HAL
• 33 inproceedingsA.Anaïs Durand, N.Nancy El Rachkidy and A.Alexandre Guitton. MADERE: Mobile Adaptive Datarate for LoRaWAN.IEEE Wireless Communications and Networking ConferenceGlasgow, United KingdomMarch 2023HAL
• 34 inproceedingsM.Mohamed El-Emary, A.Ali Ranjha, D.Diala Naboulsi and R.Razvan Stanica. Energy-Efficient Task Offloading and Trajectory Design for UAV-based MEC Systems.2023 19th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)WiMob 2023 - 19th International Conference on Wireless and Mobile Computing, Networking and CommunicationsMontreal, CanadaIEEEJune 2023, 274-279HALDOI
• 35 inproceedingsC.Carlos Fernández Hernández, G. H.Gwendoline Hochet Derévianckine, A.Alexandre Guitton, O.Oana Iova and F.Fabrice Valois. Indoor Performance Evaluation of LoRa 2.4 GHz.IEEE Wireless Communications and Networking ConferenceGlasgow, United KingdomMarch 2023HAL
• 36 inproceedingsJ. A.Juan Andrés A Fraire, A.Alexandre Guitton and O.Oana Iova. Recovering Headerless Frames in LR-FHSS.International Conference on Embedded Wireless Systems and Networks (EWSN)International Conference on Embedded Wireless Systems and NetworksRende, ItalySeptember 2023, 1-11HALback to textback to text
• 37 inproceedingsO.Olivier de Jonckère, J. A.Juan A Fraire and S.Scott Burleigh. Enhanced Pathfinding and Scalability with Shortest-Path Tree Routing for Space Networks.ICC 2023 - IEEE International Conference on CommunicationsRome, ItalyIEEEMay 2023, 4082-4088HALDOI
• 38 inproceedingsH.Hnin Pann Phyu, D.Diala Naboulsi, R.Razvan Stanica and G.Gwenael Poitau. Towards Energy Efficiency in RAN Network Slicing.LCN 2023 - IEEE 48th Conference on Local Computer NetworksDaytona Beach, United StatesOctober 2023HAL
• 39 inproceedingsG.Geymerson S. Ramos, G.Gean Santos, D.Douglas L. L. Moura, D.Danilo Fernandes, F.Fabiane Queiroz, R.Rosso Osvaldo A., R.Razvan Stanica and A.Andre Aquino. Left on read: Human behavior characterization based on messaging service applications.NetMob 2023: Book of Abstracts.NetMob 2023: Book of AbstractsMadrid, SpainOctober 2023HAL
• 40 inproceedingsZ.Zhiyi Zhang, R.Razvan Stanica and F.Fabrice Valois. Movable Base Stations in Mobile Networks for Emergency Communications.PIMRC 2023 - IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio CommunicationsToronto, CanadaSeptember 2023HAL
• 41 inproceedingsS.Stéphane d'Alu, H.Hervé Rivano and O.Olivier Simonin. TDoA for in-flight relative localization in UAV swarm using Ultra-Wide Band.CEUR Workshop ProceedingsIPIN 2023 - 13th International Conference on Indoor Positioning and Indoor NavigationIPIN-WiP 2023 Indoor Positioning and Indoor Navigation - Work-in-Progress Papers 2023Nuremberg, GermanySeptember 2023HAL

National peer-reviewed Conferences

• 42 inproceedingsC.Carlos Fernández Hernández, G. H.Gwendoline Hochet Derévianckine, A.Alexandre Guitton, O.Oana Iova and F.Fabrice Valois. On a testé pour vous : LoRa 2.4 GHz à l'intérieur.CoRes 2023 - 8èmes Rencontres Francophones sur la Conception de protocoles, l'évaluation de performances et l'expérimentation de Réseaux de communicationCoRes 2023 - 8èmes Rencontres Francophones sur la Conception de protocoles, l'évaluation de performances et l'expérimentation de Réseaux de communicationCargese, FranceMay 2023HALDOIback to text
• 43 inproceedingsJ. A.Juan Andrés A Fraire, A.Alexandre Guitton and O.Oana Iova. LR-FHSS : j'ai perdu l'entête.CoRes 2023 - 8èmes Rencontres Francophones sur la Conception de protocoles, l'évaluation de performances et l'expérimentation de Réseaux de communicationCoRes 2023 - 8èmes Rencontres Francophones sur la Conception de protocoles, l'évaluation de performances et l'expérimentation de Réseaux de communicationCoRes 2023 - 8èmes Rencontres Francophones sur la Conception de protocoles, l'évaluation de performances et l'expérimentation de Réseaux de communicationCargese, FranceMay 2023HAL

Scientific book chapters

• 44 inbookH.Hervé Rivano. Smart cities ou human city, gouverner la ville par les data.Maîtriser l’IA au service de l'action publiqueUne responsabilité individuelle et collectiveAu fil du débat-Action publiqueBerger LevraultJanuary 2023HAL

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

• 45 proceedingsP.Prosper ChemouilM.Muge SayitX.Xiaoming FuD.Diala NaboulsiC.Cihat ÇetinkayaR.Razvan StanicaProceedings of the 2023 International Conference on the Network of the Future.IEEEOctober 2023HALDOI

Reports & preprints

• 46 miscA.Alexandre Guitton, M.Megumi Kaneko and N. E.Nancy El Rachkidy. Optimality and Approximation Ratios of Demodulator Allocation Strategies in LoRa Multi-Gateway Networks.July 2023HALDOI
• 47 miscL.Lucas Magnana, H.Hervé Rivano and N.Nicolas Chiabaut. A DRL solution to help reduce the cost in waiting time of securing a traffic light for cyclists..November 2023HAL
• 48 reportM.Mina Rady, O.Oana Iova and H.Hervé Rivano. Faster is not Always Better: Cost of High Bit-Rates in Wi-Fi Networks.RR-9519CITI - CITI Centre of Innovation in Telecommunications and Integration of services; Inria AgoraSeptember 2023HAL

Scientific popularization

• 49 articleW.Weixuan Xiao, N.Nancy El Rachkidy and A.Alexandre Guitton. Signaux radio superposés : problème et solution.La Minute RechercheMarch 2023HAL