RESEARCH CENTRE

Inria Centre
at the University of Lille

2023
ACTIVITY REPORT

Project-Team

FUN

self-organizing Future Ubiquitous Network

DOMAIN

Networks, Systems and Services,
Distributed Computing

THEME

Networks and Telecommunications

Contents

Project-Team FUN

1 Team members, visitors, external collaborators

2 Overall objectives

3 Research program

3.1 Research axes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.1 Frugality and opportunism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.2 Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.3 Interconnectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 Application domains

5 Social and environmental responsibility

6 Highlights of the year

7 New software, platforms, open data

7.1 Open data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

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8 New results

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7
8.1 Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7
8.2 Non conventional communication paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
8.2.1 Visible Light Communication (VLC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
8.2.2 Reconfigurable Intelligent Metasurfaces . . . . . . . . . . . . . . . . . . . . . . . . . .
9
8.3 Data and data-based knowledge extraction for networking . . . . . . . . . . . . . . . . . . .
8.4 Digital agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
8.5 Vehicular communications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.6 Leveraging BLE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

9 Partnerships and cooperations

12
9.1 International initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
9.1.1 Associate Teams in the framework of an Inria International Lab or in the framework

9.2 International research visitors

of an Inria International Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
9.2.1 Visits of international scientists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
9.2.2 Visits to international teams
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
9.3.1 Horizon Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
9.3.2 Other european programs/initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
9.4 National initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
9.5 Regional initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

9.3 European initiatives

10 Dissemination

19
10.1 Promoting scientific activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
10.1.1 Scientific events: selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
10.1.2 Journal
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
10.1.3 Invited talks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
10.1.4 Scientific expertise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
10.2 Teaching - Supervision - Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
10.2.1 Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
10.2.2 Supervision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
10.2.3 Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
10.3 Internal or external Inria responsibilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

11 Scientific production

11.1 Publications of the year
11.2 Cited publications

23
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Project FUN

1

Project-Team FUN

Creation of the Project-Team: 2013 July 01

Keywords

Computer sciences and digital sciences

A1.2.1. – Dynamic reconfiguration

A1.2.3. – Routing

A1.2.5. – Internet of things

A1.2.6. – Sensor networks

A1.2.8. – Network security

A1.4. – Ubiquitous Systems

A1.6. – Green Computing

A5.10.6. – Swarm robotics

Other research topics and application domains

B3.5. – Agronomy

B3.6. – Ecology

B5.1. – Factory of the future

B5.9. – Industrial maintenance

B6.4. – Internet of things

B7.2.2. – Smart road

B8.1. – Smart building/home

B8.1.2. – Sensor networks for smart buildings

B8.2. – Connected city

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Inria Annual Report 2023

1 Team members, visitors, external collaborators

Research Scientists

• Nathalie Mitton [Team leader, INRIA, Senior Researcher, HDR]

• Valeria Loscri [INRIA, Researcher, HDR]

Post-Doctoral Fellows

• Adriana Arteaga Arce [INRIA, Post-Doctoral Fellow]

• Carol Habib [INRIA, from Oct 2023]

• Nassima Merabtine [INRIA, Post-Doctoral Fellow, until Feb 2023]

• Aya Moheddine [INRIA, Post-Doctoral Fellow, from Jul 2023]

• Damien Wohwe Sambo [INRIA, Post-Doctoral Fellow]

• Selma Yahia [INRIA, Post-Doctoral Fellow, from Aug 2023]

PhD Students

• Ildi Alla [INRIA]

• Aymen Salah Eddine Bouferroum [INRIA, from Oct 2023]

• Hazem Chaabi [INRIA]

• Selina Cheggour [UNIV LILLE]

• Jana Koteich [INRIA]

• Nina Santi [INRIA]

• Marwa Slimene [INRIA, from Jun 2023]

• Jiali Xu [INRIA, from Mar 2023]

Technical Staff

• Lucille Colin [INRIA, from Sep 2023, Project Manager]

• Solenne Fortun [INRIA, Project Manager]

• Etienne Profit [INRIA, Engineer]

• Prakriti Saxena [INRIA, Engineer, until Aug 2023]

Interns and Apprentices

• Simon Lacan [INRIA, Intern, from May 2023 until Aug 2023]

• Tom Mathieu Ruckstuhl [UNIV LILLE, Intern, from May 2023 until Jun 2023]

Administrative Assistant

• Anne Rejl [INRIA]

Project FUN

Visiting Scientists

3

• Gerardo Hernandez Oregon [Instituto Politécnico Nacional de Mexico, from Feb 2023 until Jul 2023,

Visiting PhD student]

• Herve Olou Babatounde [University of Benin, from May 2023 until Jul 2023, Visiting PhD student]

2 Overall objectives

With the foreseen increase of communicating devices around the world, many challenges will arise.
Among them, the most predominant ones are certainly the scarcity of the medium, the energy consump-
tion, the lack of interoperability and the security of these devices and their data.

Our objectives are to address these different challenges for the self-organization of these Future
Ubiquitous Networks. Our focus will be set on wireless heterogeneous communicating objets that feature
different limitations and constraints such as hardware limitations (low computing and memory storage
capacities), limited energy, potentially high mobility or hostile environment. By wireless, we mean any
communication with no wire. Objects could thus communicate through traditional RF transmissions
or any alternative way such as visible light communication (VLC) or molecular technologies. They can
be heterogeneous in terms of hardware processing, mobility patterns (mobility can be undergone or
controlled, unknown or predictable), communication technologies, etc. For all these families of devices,
we will design holistic communication protocols to allow them to efficiently function and cooperate in a
harmonious energy- and data-priority aware fashion. These protocols will focus on low communication
layers (PHY, MAC and NET) and combine opportunistically heterogeneous device features to make a
global efficient behavior emerge.

The goal of the FUN project team is to leverage the heterogeneity of the new communicating
devices to override major rising issues. Heterogeneity and mobility will be seen as opportun-
ities and strengths rather than flaws and exploited. Our protocols will foster the cooperation
between devices in a secure, energy efficient and frugal way.

3 Research program

Objectives and methodology

To achieve our main objectives, we will mainly apply the methodology depicted in Figure 1 combining
both theoretical analysis and experimental validation. Mathematical tools will allow us to properly
dimension a problem, formally define its limitations and needs to provide suitable protocols in response.
Then, they will allow us to qualify the outcome solutions before we validate and stress them in real
scenarios with regards to applications requirements. For this, we will realize proofs-of-concept with
real scenarios and real devices. Differences between results and expectations will be analyzed in return
in order to well understand them and integrate them by design for a better protocol self-adaptation
capability.

3.1 Research axes

To reach this overall objective, we will develop our research around the three following axes: i) Frugal-
ity and opportunism, ii) Security and iii) Interconnectivity. Note that these axes are not completely
independent nor hermetic. A transversal axis will be the deployment and set up of experimental testbeds.

3.1.1 Frugality and opportunism

As the objects we consider are resource-limited and that they use a rare resource to communicate (wireless
medium), all our solutions must be frugal and use as little resources as possible. A way to alleviate the
energy consumption and the medium utilization is to reduce the data to send and/or to smartly decide
when to send it, by what mean and to whom without jeopardizing the accuracy and completeness of the
data. When to send a data can indeed impact the resource utilization since in a dynamic environment,

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Inria Annual Report 2023

Figure 1: Methodology to be applied in FUN.

some interference could appear at different times; in a mobile environment, a data could be carried
rather than transmitted; in an energy-harvesting network, the amount of available energy could grow.
We thus intend to closely analyse and understand interference impacts on different environments and
contexts on one hand (as the research initiated in LumiCar, EthiCam, AgriNET) and to exploit them in the
design of our protocols.

Deciding what data to send allows for a data reduction and resource savings. To do so, we will use
machine learning techniques (e.g. Thompson sampling, Bayesian approaches, linear approaches, ARMA,
Pearson sampling etc) that we will adapt to fit the specific context of the applications. The idea is to
propose predictive algorithms to "guess" a data rather than transmitting it. This is among others what we
are investigating in the AgriNET project.

In case of the availability of multiple communication technologies, the choice of this technology
will impact the global system since all technologies do not provide the same QoS performances (delays,
throughputs, etc) with different energy consumptions and do not face interferences the same way
depending on the environment. We will thus analyse and understand all these specificities to combine
them to get the best performances.

In all above mentioned cases, we will try to provide time and space depend protocols as frugal as
possible but still meeting the application requirements and expectations. This will be done by opportun-
istically leveraging network particularities (multiple technologies, mobility, energy-harvesting, etc) based
on experimental-driven behavioral analysis, as initiated with the collaboration with Sencrop.

3.1.2 Security

Security of wireless transmissions is a rising issue that gains importance with the increase of wireless
devices. Our team has just started research work in security but we will pursue our efforts. Our goal
will be to secure the wireless communications in different ways. Indeed, traditional security techniques
(cryptography, firewalls, etc) cannot be applied in FUN because of their pervasive feature and limited
resources. In terms of Security, we will focus on the lowest layers of the communication stack in order to
first identify attacks that may appear at these levels and proposes i) recovering and healing solutions and
ii) new solutions that are robust by design.

At the MAC layer, we will for instance investigate denial of sleep-like attacks that aim to make nodes
deplete their energy quickly. At NET layer, we will investigate different routing protocols that are able to
detect an abnormal behavior of a neighbor node to then exclude it from any network operation. This has
obviously to be done locally and in a distributed way. In all cases, the same methodology will be apply:

Project FUN

5

observe, understand and model, to then identify the threat or the malicious entity and finally heal. In
some case, we can leverage the characteristics of the communication technology to reinforce the security
aspect, such as VLC that may allow Line-of-Sight (LOS) communications and for which certain types of
attacks that can be effective for "traditional" wireless systems (i.e., jamming attacks) cannot be easily
applied. The works initiated in the framework of the H2020 CyberSANE project, in the DGA grant and in
DEPOSIA project, fall within this perspective.

3.1.3 Interconnectivity

Another challenge faced by FUN is their interconnectivity to traditional networks such as Internet and
the data offloading. Because of their limited capacity, FUN devices may need to call for remote services.
These latter are usually hosted in the cloud. But being served by the cloud implies sometimes long latency
and uselessly congest the wired network. We will thus investigate how to get these services closer to the
FUN devices to alleviate the energy consumption, reduce latency and network congestion. This will
go from edge and mobile edge deployments to service distribution over more powerful heterogeneous
devices. Our research will analyse devices needs and estimate in time and space the services to be
deployed. When the service is expected to be temporary, mobile edge services could be deployed and so
our investigations will include the self-deployment techniques. When some already deployed wireless
devices feature more capacity, we can leverage this node heterogeneity to distribute the services over
these nodes. The research conducted towards this third objective will call for adaptation of machine
learning techniques to predict needs, to mobility modeling and cross-layer communication protocols.
This has been initiated in the DRUID-NET project.

4 Application domains

The FUN research can be applied in various applications. We only cite here the ones on which we
currently focus.

• Smart Agriculture: Wireless sensors are more and more deployed in remote fields and livestock for
an accurate monitoring. This generates new challenges in terms of reliability, energy consumption
and range as investigated in the D4SC and Agrinet projects.

• Vehicular networks: vehicles become smarter and smarter, providing new useful services. But
communications between vehicles on one hand and between vehicles and road infrastructures on
the other hand raise a lot of challenges as investigated in the CONCESE project.

• Smart infrastructures: FUN research can also apply to different urban and civil infrastructure like

road monitoring (as in the DEFI with CEREMA) or Smart Grids.

• Logistic and traceability: RFID and IoT are the key technologies to enable large scale traceability.

They are for instance investigated in the GoodFloow project.

• Post disaster recovery: New services of different kinds (communications, processing, context
analysis) need to be deployed quickly and efficiently after a disaster in order to support rescue
operations. This requires adaptable and flexible resource deployment such as investigated in
NEPHELE and DRUID-NET projects.

5 Social and environmental responsibility

In all our research, we really care to the low energy consumption by design but also to the final goal,
paying a special attention to applications that support environement, decarbonisation or social concerns.
This is reflected by the main topic of most of our collaborative projects.

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Inria Annual Report 2023

6 Highlights of the year

European Commission’s Innovation Radar identified Inria FUN in the project as one of the 3 ’Key Innovat-
ors’ in the development of the Integrated incident handling and response for critical infrastructure in the
CyberSane project.

7 New software, platforms, open data

We believe open software and open data collection or generation tools are mandatory in our research, to
ensure reproducibility and repeatability. Therefore we have built two main software tools. The first one
relies on the FIT IoT LAB open testbed and allows for the generation of network data. The second one
allows for the collection of real communication traces. Both our tools are made available on open gitlab
and the dataset either generated or collected are freely shared. The software tools call to the enrichment
of these datasets.

7.1 Open data

Sisyphe

Participants: Nathalie Mitton (contact person), Nina Santi.

The Sisyphe tool [19] relies on the FIT IoT-Lab large scale testbed and state-of-the-art software
engineering techniques to produce, collect and share artifacts and datasets in an automated way. This
makes easy to track the impact of software updates or changes in the radio environment both on a small
scale, e.g. during a single day, and on a large scale, e.g. during several weeks. By providing both the source
code for the trace generation as well as the resulting datasets, we hope to reduce the learning curve to
develop such applications and encourage reusability as well as pave the way for the replication of our
results. While we focus in this work on IoT networks, we believe such an approach could be used in many
other networking domains.

All generated dataset and open software are available here and in Zenodo. It has been then extended

to include mobility in data generation. This extension is available here.

PILOT

Participants:

Jana Koteich, Nathalie Mitton (contact person).

PILOT [18] dataset is a Privacy-preserving data collectIon tool of wireLess cOmmunication Techno-
logies. The collected dataset is a collection of four jointly collected information in different mobility
contexts. It includes three wireless communication technologies: WiFi probe-responses, BLE (Bluetooth
Low Energy) beacons, and LoRa (Long Range Radio) packets, plus additional information: Acceleration,
Roll, and Pitch, all collected at the same time. We provide the keys to reproduce such data collection and
share the datasets already collected. The dataset is collected for approximately 90 hours, with a size of 200
MB using FiPy devices from Pycom and it is uploaded to GitHub. The dataset’s utility is validated through
the application of a classification machine learning model [14] that determines the real-life situation
of devices through the communication links monitored in different scenarios with an accuracy of 94%.
Thus, we believe that such dataset is important for human mobility studies and applications of integrated
sensing systems since it offers a new form of a classified collected data that does not exist in the already
published datasets.

All collected dataset and open software are available here.

Project FUN

8 New results

8.1 Security

7

Participants:

Valeria Loscri, Selma Yahia, Nassima Merabtine, Ildi Alda, Jiali Xu,
Aya Moheddine, Aymen Bouferroum, Nathalie Mitton.

Wireless networks have enabled the development of new communication paradigms, including
cellular networks and the Internet of Things (IoT). Due to the openness of the wireless medium, these
new paradigms present new challenges in terms of resource allocation, interference management, and
novel attack strategies. To deal with these challenges, several wireless communication protocols envision
the use of different frequency bands for communications, and each frequency band is separated into
channels. Exploiting this paradigm, channel hopping has been proposed to regularly or adaptively change
the communication channel assigned to nodes in the network to limit both collisions and interference
generated by neighboring devices. Several standard network protocols use channel hopping methods,
with examples such as 802.15.4 protocol with the Time Slotted Channel Hopping (TSCH) or Bluetooth
with the Frequency Hopping Spread Spectrum (FHSS) and Adaptive Frequency Hopping Spread Spectrum
(AFH). Channel Hopping schemes are also developed in cognitive radio to limit the noise effects and
improve the channel saturation problem. Channel hopping is also widely applied in drones technology
and it is normally employed to mitigate the physical attacks (e.g., jamming attacks). In [11], we consider
a smart jamming attack, without needing of previous knowledge on the victim’s behavior. The main
objective is to learn the victim’s channel hopping strategy form real-time channel measurements. The
validation is based on real experiments on a testbed created from scratch in our laboratory. The evaluation
is comparing different appraoches, such as random channel hopping, incremental channel hopping, and
show the superiority of our smart approach in terms of effectiveness, response time and accuracy. We are
also extending this approach to drones systems, by considering DJI nodes, implementing ad-hoc channel
hopping methods. Of course, the channel hopping method is prone to specific attacks, and if a malicious
node has the willingness to hinder a correct communication between a transmiutter and a receiver, it can
exploit it to create Denial Of Service (DoS) attacks. For these reasons, it is paramount that the channel
selection is based on advanced methods. In [4] we propose a channel selection model able to assist
wireless nodes in choosing the best channel to transmit on, that is suitable for wireless devices and does
not require standard modifications. The proposed model, developed for wireless technologies based on
the association phase, can be implemented in several wireless technologies, spanning from IEEE 802.15.4
to Z-Wave, just to cite a few. We were inspired by the concept of trustworthiness and took advantage
of the well-known trust management techniques. In this scenario, the communication between nodes
involves two different roles: the first represents the trustor, and it has to trust the other one, which
depicts the trustee and provides the required data. However, misbehaving devices can perform different
types of attacks and can disrupt communications for their own gain. The trustworthiness management
techniques have to solve the essential issue to detect which channel is affected by malicious behaviours
and so lead the nodes to successful collaboration. In particular, we proposed a trust management model,
based on experience and recommendations, able to assist wireless nodes in channel selection. This
appraoch does not demand any change in the standard. The different behaviors of jamming attacks have
been considered and analyzed and we proposed a new one, to test the resiliency of the our proposed trust-
based approach. The approaches considered above, make clear the need of a consistent organization and
classification of the different types of attacks in wireless systems, that are increasing in terms of types and
become more and more evolved. This categorization of attacks has been the core of [6]

8.2 Non conventional communication paradigms

Participants:

Valeria Loscri.

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Inria Annual Report 2023

8.2.1 Visible Light Communication (VLC)

It is a well recognized matter of fact that the Internet of Everything (IoE) paradigm main limitation is
represented by the exiguous wireless resources. In the last decade, Optical Wireless Communication
Systems (OWCSs) have risen as a green and effective solution to alleviate the spectral scarcity and boost the
ubiquitous deployment and usage of IoE devices. The significant advances in optoelectronic technology
have made Light Emitting Diodes (LEDs) and photodetectors (PDs) inexpensive, and efficient hardware to
equip optical transceivers. Furthermore, the emission of LEDs can be conveniently managed to provide
the illumination service jointly with wireless connectivity. One of the key features of OWCSs is they are
Intensity-Modulation/Direct-Detection (IM/DD) systems, requiring high energy efficient modulation
techniques. Among the different modulation schemes, one of the most widespread is On-Off Keying
(OOK), as a special case of Pulse-Amplitude Modulation (PAM) employing only two transmit signal power
levels, one of which is set to zero. In general, even though PAM is very suitable for OWCSs, its main issue
is related to the growth of the electrical/optical energy per bit, with the increase of modulation order,
necessary to guarantee a certain Bit Error Rate (BER). A higher level of energy efficiency can be achieved
with the adoption of orthogonal modulation schemes, although with a negative impact on spectral
efficiency. Frequency-Shift Keying (FSK) belongs to the orthogonal modulation schemes category. Its
main drawback in the context of OWCSs is represented by its bipolar characteristics, however the variant
of FSK based on Direct-Current (DC) offset, namely DC-FSK, allows to obtain a scheme compatible with
the IM/DD approach.

Based on these premises, it is clear that each modulation scheme has its own strengths and weaknesses.
Hence, combining different techniques would be a promising approach to capitalize on the benefits and
mitigate drawbacks. This is the main subject investigated in [5]. The main novelty of this work is that we
propose a multi-modulation scheme relying on the combination of non-orthogonal PPM, PAM and FSK to
leverage the specific features and smartly mitigate the main drawbacks of each modulation. Such popular
schemes are merged in a whole, novel framework, in order to efficiently exploit the time, amplitude and
frequency features of the different schemes. The goal is to achieve performance improvements in terms
of spectral and power efficiency with respect to pure modulations, providing also a constant illumination
level that represents a fundamental requirement in real-world indoor VLC systems.

8.2.2 Reconfigurable Intelligent Metasurfaces

In recent years, mmWave technology has acquired an increasing interest to be exploited in future wireless
cellular communications, such as in the sixth generation (6G) network scenarios. Due to the large band-
width, very high data rates in the order of gigabit per second (Gbps) are expected to be achieved with
much increased capacity, as compared to other existing wireless communication systems. Furthermore,
since mmWave links present high directionality feature, an efficient spatial and frequency reuse can be
obtained, with the possibility to exploit Line-of-Sight (LOS) links that are very beneficial for interference
control. However, some important issues related to the specific propagation features of mmWave signal
need to be considered and addressed in order to exploit the enormous potentiality of this technology.
Among the main challenges with mmWave we remind the significant path loss that the mmWave sig-
nals experience, the blockage due to obstacles, the atmospheric attenuation, as well as harsh weather
conditions such as rain, absorption by water vapors, and oxygen, that degrade the mmWave channel.
Recently, in order to address the main issues of mmWaves technology, the concept of Reconfigurable
Intelligent Meta- Surface has been introduced in the research community. Concerning the optimiza-
tion of RIM-based systems, previous contributions in literature have regarded the feasibility to achieve
beamforming based on RIM exploitation, by proposing optimization approaches. Other approaches have
been proposed to relax the associated feedback overhead and are mostly based on statistical Channel
State Information (CSI) and still relay on channel-state and on channel control to steer the RIM beams.
In [3], the main aim is to relax the control channel and the high overhead associated to, by exploiting
a pre-existing and well-deployed infrastructure, namely the cameras that are nowadays mas- sively
deployed in the modern cities. Basically, we exploit the concept of View to Communicate V2C, by means
of a CV- based approach to monitor traffic load in a real network scenario. The CV solution is introduced
together with a RIM-based sub-system, performing beam steering func- tionality in the mmWave working
frequency. The developed framework, BEST-RIM is evaluated by the means of Monte-Carlo approach,

Project FUN

9

and the impact of the Computer Vision as well as the Genetic Algorithm integrate in the appraoch and
used to compute the most suitable solution are evaluated. In [16] we also consider a mmWave RIM-based
infrastructure, but we better focus on beem-steering capabilityes. In particular, we propose a novel
reconfigurable intelligent metasurface able to perform beam-steering in mmWave frequencies. It has the
advantage to be insensitive to the angle of incidence up to 75◦. The control of the direction of beams
generated by the metasurface towards a target receiver, is realized by the means of a Particle Swarm
Optimization (PSO) algorithm. Finally, our metasurface is placed inside a system including a base station
and a mobile receiver and the impact of the interferers on the ability of the metasurface of tracking the
user is evaluated.

8.3 Data and data-based knowledge extraction for networking

Participants:

Jana Koteich, Nathalie Mitton, Nina Santi.

The ubiquity of mobile devices equipped with radio communication technologies has made large-
scale data collection on human mobility commonplace. Therefore, with the lack of datasets, data
collection and publication are raising new scientific questions. This is why we developed the PILOT
dataset and its privacy-preserving data collection methodology for wireless communication technologies
[18]. The dataset is a collection of four pieces of information collected together in different mobility
contexts. It includes three wireless communication technologies: WiFi beacons, Bluetooth Low Energy
(BLE) beacons and Long Range Radio (LoRa) packets, as well as additional information that includes:
Acceleration, Roll and Pitch, all collected at the same time. We provide the keys to replicate this data
collection. The dataset is collected for about 60 hours, with a size of 150 MB using Pycom’s FiPy devices
and is uploaded to GitHub. We believe that the combination of the different types of information collected
in different mobility scenarios constitutes a new generation of a rich dataset.

We then leverage this dataset to propose a new approach for mobility classification using a real dataset
of WiFi and BLE beacons collected over one year for around 90 hours in different scenarios and conditions
[14]. The first model (B-model) aims to identify the status of a device if stationary or mobile. Then a
complementary model (M-model) is applied to determine a more precise real-life situation of the device,
which could be a Home, Office, Bus, Train, etc. The results show that decision- tree-based ensemble ML
algorithms like LGBMClassifier and XGBClassifier gave the best results, in terms of accuracy and f1 score
for both models with an accuracy of 99% and 94% respectively, confirming the capability of classifying
mobility context from only WiFi and BLE data. We believe that such an approach could be leveraged
for studying human mobility and an important step towards the large deployment of mobility-based
applications by leveraging everyday mobile phones.

8.4 Digital agriculture

Participants: Carol Habid, Adriana Arteaga Arce, Jana Koteich, Nathalie Mitton,

Damien Wohwe Sambo.

There exist several ways to reduce energy consumption in wireless sensor networks in general and in
particular for digital agriculture applications. We have focused on data reduction approach, relying on
the observation that agriculture data can be correlated or easyly estimated. The lead idea being that if
two phenomena are correlated, then maybe we could estimate the way one goes based on the way the
second one do. This effectively reduces the amount of data nodes may have to transmit while preserving
the information.

In [2], we introduce two mechanisms to reduce the overall number of frames sensed and sent to
the sink. The first approach is applied on each sensor node, where the FRABID algorithm, a joint data
reduction, and frame rate adaptation on sensing and transmission phases mechanism is introduced. This
approach reduces the number of sensed frames based on a similarity method. The aim is to adapt the
number of sensed frames based on the degree of differ- ence between two consecutive sensed frames

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Inria Annual Report 2023

in each period. This adaptation technique maintains the accuracy of the video while capturing frames
holding new information. This approach is validated through simulations using real data-sets from video
sensors. The results show that the amount of sensed data is reduced by more than 70% compared to
a recent algorithm while guaranteeing the detection of all the critical events at the sensor node level.
The second approach exploits the Spatio-temporal correlation between neighboring nodes to reduce
the number of captured frames. For that purpose, Synchronization with Frame Rate Adaptation SFRA
algorithm is introduced where overlapping nodes capture frames in a synchronized fashion every N-1
periods, where N is the number of overlapping sensor nodes. The results show more than 90% data
reduction, surpassing other techniques in the literature at the level of the number of sensed frames by
20% at least.

Then, we have proposed in [13] a similar method, but here not only limited to a pair of nodes. With
our scheme we can reduce the traffic of several nodes over a whole multihop route of communications in
a network. We have implemented that scheme and experimented with real hardware which shows good
results.

Finally, we focused on a Wireless Underground Sensor Network (WUSN) [9] for agriculture, where
challenges arise from signal attenuation in the soil and the limited battery that powers the sensor nodes.
Due to the attenuation of the signal in the ground, the reception or loss of the sent data depends on the
ground conditions, which can change dynamically. However, in existing WUSNs, each node sends the
data collected in each round regardless of the signal attenuation. It is well demonstrated that sensor
nodes consume the most energy during transmission. Obviously, transmission without receiving any
data signifiicantly reduces the lifetime of a sensor node useless. This paper presents a novel fuzzy-based
decision-making solution called FuzDeMa that reduces energy consumption by anticipating data losses
before transmission. To do so, FuzDeMa assesses in real time the loss or the reception of a packet
according to the in-situ node’s environments before its transmission and decides whether to send or
not the packet based on the computed reliability. To validate the proposed approach, we embed it into
a dedicated underground node called the MoleNet and realized real experimentations firstly with an
existing dataset and secondly, with precision-measuring equipment to estimate the energy consumption.
The results revealed the possibility of prolonging the lifetime of the sensor node by saving up to 81.7876
microJ in a single round. Additionally, FuzDeMa shows the ability to save energy for up to 46 of additional
revolutions, thus extending the life of the sensor node to 32.85% for 140 real transmission cycles. An
analytical generalization of FuzDeMa is provided regardless of a specific dataset or sensor node. Thus, we
provided the conditions for a random dataset to save the energy with any sensor node that implements
FuzDeMa during transmissions.

8.5 Vehicular communications

Participants:

Bingying Wang, Nathalie Mitton, Valeria Loscri.

The connected vehicle is becoming a reality, and both centralised applications provided through
telecommunication infrastructure, and cooperative applications achieved directly by the vehicles through
vehicle-to-vehicle communications are gaining a lot of interest from the public. Though several solutions
have been investigated to ensure identification and privacy protection of vehicles participating in these
applications, only a few works address the recording of exchanged messages from an audit perspective,
especially in the context of vehicle-to-vehicle communications only. Therefore we have proposed a review
of the literature on vehicular communications [10], and explores particularly the solutions envisaged
for audit in this context, such as the Blockchain technology. We also point out the most challenging
issues that should be addressed in order to achieve an effective deployment of this latter in vehicular
communications, especially in the vehicle-to-vehicle communication context, which should help in
developing an effective Blockchain-based audit strategy.

Broadcasting is an important routing strategy for message delivery in a VANET. However, the broadcast
storm caused by loads of duplicate data packets can be severe, which leads to intense contention among
vehicle nodes and a large number of dropped packets. In this case, the efficiency of message delivery is
limited. In [17] we consider a broadcast routing protocol specially designed for urban areas with dense

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traffic and a huge amount of data traffic, and proposes a Preferred-Zone based broadcast (PreZcast)
protocol. To alleviate the broadcast storm and improve the efficiency of message delivery, PreZcast only
allows neighbors located within a Preferred Zone (PreZ) of a source node to rebroadcast a received packet.
The PreZ is chosen based on the initial location and the distribution of two-hop neighbors of the source
node. To further validate PreZcast in a more realistic and irregular topology, we evaluate PreZcast with
real datasets issued from Bologna road traffic. Moreover, MultiPoint Relay (MPR) is introduced to further
reduce duplicate packets in the network. Simulation results show that as compared with the Flooding
protocol, PreZcast approximately improves 15% of broadcast efficiency and reduces 65% of packets
transmitted with 5% more energy consumption, while PreZcast with MPR improves 10% of broadcast
efficiency and reduces 70% of packets transmitted with only 0.5% more energy consumption.

In a similar approach, we have proposed an Intra-Platoon Cooperative Resource Selection (InP-CRS)
scheme for frequency-time resource selection to support reliable intra-platoon message delivery [8]. The
proposed InP-CRS scheme is based on the standardized sensing-based semi-persistent scheduling (SPS)
scheme designed for C-V2X mode 4 and is intended to address the hidden-node problem in intra-platoon
communication. Specifically, the InP-CRS scheme introduces an intra-platoon cooperative mechanism, in
which the last member of a platoon needs to reports the frequency-time resource occupation information
of the platoon’s hidden nodes to the platoon leader (PL) so that the PL can exclude those resources
occupied by the hidden nodes of the platoon during its resource selection. In this way, potential packet
collisions caused by the hidden nodes of a platoon can be largely reduced. Simulation results show that
the proposed InP-CRS scheme can effectively improve the reliability of intra-platoon message delivery in
terms of the successful broadcast probability of a PL as compared to the standardized sensing-based SPS
scheme.

Obstacle detection is a tool adopted in vehicular safety applications, aiming to detect a moving
obstacle in an area of interest with the highest accuracy. Different sensors are used for this aim, such
as LiDAR devices mounted on board of a vehicle that capture images of the surrounding environment.
Extending the number of LiDAR sensors can be useful to improve the obstacle detection accuracy, since
multiple images are captured from different distances and directions, and this represents an interesting
approach, specially in case of dense networks with cooperative nodes. In [1], we present MuSLi technique,
aiming to (i) provide an accurate obstacle detection and (ii) forward alert messages to other cars in the
network, in case of correct detection of a pedestrian crossing the street. MuSLi relies on the connected
content islands scenario, where each vehicle defined as a content island subscribes to a service in order
to receive and share published messages. Specifically, the road safety service allows the detection of an
obstacle through multiple LiDAR sensors from neighboring cars. Furthermore, we investigate the fastest
transmission mode among those defined in the C-V2X releases to alert the presence of a pedestrian to
the other approaching cars. The proposed technique provides the distances by the crossroad in which is
better to use V2V, V2I or V2N according to the environment, the scheduling technique and the measured
interference.

Social features are affecting different application areas, from traditional online social networks to
economical networks, as well as the study of epidemical behaviors of pandemics and diseases. From
the information point of view, also the Internet paradigm has been revised according to social behaviors
of nodes, showing intrinsic properties that have allowed the definition of the Social Internet of Things
paradigm. Furthermore, considering vehicular networks, social features have been spreading their
influence, and defined the concept of Vehicular Social Networks, where mobile nodes show predictable
social behavior. In this context, all the networking concepts should be updated accordingly, taking
into account node social aspects and interactions. In [7], we discuss the open challenge of how we
should define a trust vehicle, relying on social networking aspects. We introduce the concept of node
trustworthiness in a vehicular environment, based on the reputation degree, computed according to real-
time interactions and past data. A node can be defined as trusted if exhibiting an acceptable reputation
degree, and being successfully able to transmit data packet in a given environment. The framework of a
network architecture for the computation of node trustworthiness degree in a vehicular scenario is also
presented.

8.6 Leveraging BLE

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Inria Annual Report 2023

Participants:

Etienne Profit, Nathalie Mitton, Damien Wohwe Sambo.

Contact Tracing (CT) is an old, recognized epi- demiological tool, and since a digital variant is now
within reach, a variety of smartphone-based solutions have been rapidly developed and deployed since
2020, with mixed results and amid controversies. Yet, achieving reliable and effective digital CT at large
scale is still an open problem. In [15], we contribute with an open source software platform on top of
which various CT solutions can be quickly developed and tested. More specifically, we design PEPPER,
which jointly leverages Bluetooth Low Energy (BLE) and Ultra Wide Band (UWB) radios for contact
detection, combined with the DESIRE privacy-preserving CT protocol. We show that PEPPER+DESIRE
can operate on cheap physical tokens based on low-power microcontrollers, opening new use-cases
with less personal, potentially disposable devices, that could be more widely used. We also evaluate the
complementarity of Bluetooth and UWB in this context, via experiments mimicking various scenarios
relevant for CT. Compared to BLE-only CT, we show that UWB can decrease false negatives (e.g., in
presence of human body occlusion), meaning that more actual contacts will be found, a key benefit from
an epidemiological viewpoint. Our results suggest that, while PEPPER+DESIRE improves precision over
state-of-the-art, further research is required to harness UWB-BLE synergy for CT in practice. To this end,
our open source platform (which can run on an open-access testbed) provides a useful playground for
the research community.

In wireless sensor networks, much energy is wasted during connecting and control processes. This
is particularly true for the neighborhood discovery process carried out in Bluetooth Low Energy (BLE)
before the communications between devices. However, the fixed duration of this process has a critical
energy cost when the number of neighbors is low or when only a few neighbors are required by the
application. In order to address this issue, we proposed a novel protocol called WUBBLE [12] to leverage
wake-up radio technology to start and end the discovery process. Wake-up radio enables additional
communications between devices with an ultra-low energy overhead. WUBBLE is validated by combining
analytical analysis and experimental measurements, and results show that half of the energy could be
gained to discover 90% of the neighbors.

9 Partnerships and cooperations

9.1 International initiatives

9.1.1 Associate Teams in the framework of an Inria International Lab or in the framework of an Inria

International Program

AGRINET

Participants:

Jana Koteich, Nathalie Mitton, Damien Wohwe Sambo.

Title: Wireless accurate monitoring for a smarter agriculture

Duration: 2021 - 2025

Partners : Stellenbosch University (South Africa)

Inria contact: Nathalie Mitton

Summary: The proposed research entails the development of a flexible, rapidly deployable, biological
data acquisition platform to create advanced agricultural monitoring and management techniques
for better natural resource management and smart farming decision making. This platform will
involve a wireless sensor network and a machine-learning based decision making tools. Sensors will
be spread over the fields to sense information on soil water and nitrate concentration, temperature
etc, and remotely communicate this data in a wireless way to the server which will provide decision

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making tools according to the kind of culture. A first objective is to create an advanced, flexible
wireless sensor network for wide area agricultural data measurement, with an adaptable dynamic
routing strategy including the considerations of various factors such as network availability, node
positioning, message priority and resource availability (typically battery capacity) in order to op-
timize data transmission reliability and utilize communication resources optimally. This particular
topology is proposed to enhance the total network coverage and to compensate for propagation
problems that are certain to occur due to the variable crop-, climatic- and vineyard topography.
A second objective to be achieved in parallel is to adapt current machine learning and pattern
recognition algorithms to obtain an area wide and in depth view of crop and soil conditions to
identify and enable optimal crop management and harvest conditions. In AgriNet, multiple inputs
from multiple nodes will be integrated into a machine learning based classification framework.
Complementary and inter-dependent data input will enable and enhance the detection of conver-
ging patterns, providing a completely new level of confidence in terms of early warning strategies
and sensing accuracy. This could be of enormous value in presenting early warning signs of disease
and other unwanted conditions for cost efficiency and increase in crop yield and quality. A third
objective is the integration of the final system (wireless sensor network and machine learning based
system) in a complete agriculture-oriented prototype. Pilot projects will be deployed during the last
year in both France and South Africa focusing on two main cultures: potato crops and vineyards in
order to stress and evaluate the AgriNet prototype.

9.2 International research visitors

9.2.1 Visits of international scientists

Riaan Wolhuter spent one week at Inria from Stellenbosch University in September 2023.

Hervé Oulu spent three months at Inria from University of Benin as a visiting PhD student.
Gerardo Hernandez Oregon from Instituto Politécnico Nacional de Mexico spent 6 months at Inria

FUN.

9.2.2 Visits to international teams

Research stays abroad

Participants:

Jana Koteich.

Visited institution: Stellenbosch University

Country: South Africa

Dates: March 15 - May 15 2023

Context of the visit: In the framework of the Agrinet project.

Participants:

Ildi Alla.

Visited institution: Irvine University

Country: USA

Dates: October 1 - December 31 2023

Context of the visit: in the framework of DEPOSIA project

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Inria Annual Report 2023

9.3 European initiatives

9.3.1 Horizon Europe

NEPHELE

Participants:

Adriana Arteaga Arce, Hazem Chaabi, Carol Habid, Nathalie Mitton.

NEPHELE project on cordis.europa.eu

Title: A LIGHTWEIGHT SOFTWARE STACK AND SYNERGETIC META-ORCHESTRATION FRAMEWORK

FOR THE NEXT GENERATION COMPUTE CONTINUUM

Duration: September 2022 - August 2025

Inria contact: Nathalie Mitton

Summary: The vision of NEPHELE is to enable the efficient, reliable and secure end-to-end orchestration
of hyper-distributed applications over programmable infrastructure that is spanning across the
compute continuum from Cloud-to-Edge-to-IoT, removing existing openness and interoperability
barriers in the convergence of IoT technologies against cloud and edge computing orchestration
platforms, and introducing automation and decentralized intelligence mechanisms powered by 5G
and distributed AI technologies.

The NEPHELE project aims to introduce two core innovations, namely:

(i) an IoT and edge computing software stack for leveraging virtualization of IoT devices at the
edge part of the infrastructure and supporting openness and interoperability aspects in a device-
independent way. Through this software stack, management of a wide range of IoT devices and
platforms can be realised in a unified way, avoiding the usage of middleware platforms, while
edge computing functionalities can be offered on demand to efficiently support IoT applications’
operations.

(ii) a synergetic meta-orchestration framework for managing the coordination between cloud and
edge computing orchestration platforms, through high-level scheduling supervision and definition,
based on the adoption of a “system of systems” approach.

The NEPHELE outcomes are going to be demonstrated, validated and evaluated in a set of use cases
across various vertical industries, including areas such as disaster management, logistic operations
in ports, energy management in smart buildings and remote healthcare services. Two successive
open calls will also take place, while a wide open-source community is envisaged to be created for
supporting the NEPHELE outcomes.

SLICES-PP

Participants:

Lucille Colin, Solenne Fortun, Nathalie Mitton.

Title: Scientific Large-scale Infrastructure for Computing/Communication Experimental Studies - Pre-

paratory Phase

Duration: September 2022 - December 2025

Inria contact: Nathalie Mitton

Summary: The digital infrastructures research community continues to face numerous new challenges
towards the design of the Next Generation Internet. This is an extremely complex ecosystem encom-
passing communication, networking, data-management and data-intelligence issues, supported by
established and emerging technologies such as IoT, 5/6G, cloud-to-edge computing. Coupled with

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the enormous amount of data generated and exchanged over the network, this calls for incremental
as well as radically new design paradigms. Experimentally-driven research is becoming worldwide
a de-facto standard, which has to be supported by large-scale research infrastructures to make
results trusted, repeatable and accessible to the research communities.

SLICES-RI (Research Infrastructure), which was recently included in the 2021 ESFRI roadmap, aims
to answer these problems by building a large infrastructure needed for the experimental research
on various aspects of distributed computing, networking, IoT and 5/6G networks. It will provide
the resources needed to continuously design, experiment, operate and automate the full lifecycle
management of digital infrastructures, data, applications, and services.

Based on the two preceding projects within SLICES-RI, SLICES-DS (Design Study) and SLICES-SC
(Starting Community), the SLICES-PP (Preparatory Phase) project will validate the requirements
to engage into the implementation phase of the RI lifecycle. It will set the policies and decision
processes for the governance of SLICES-RI: i.e., the legal and financial frameworks, the business
model, the required human resource capacities and training programme. It will also settle the final
technical architecture design for implementation. It will engage member states and stakeholders
to secure commitment and funding needed for the platform to operate. It will position SLICES as
an impactful instrument to support European advanced research, industrial competitiveness and
societal impact in the digital era.

MLSysOps

Participants:

Aya Moheddine, Valeria Loscri, JiaLi Xi.

Title: Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum

Duration: January 2023 - December 2025

Inria contact: Valeria Loscri

Summary: MLSysOps will achieve substantial research contributions in the realm of AI-based system
adaptation across the cloud-edge continuum by introducing advanced methods and tools to en-
able optimal system management and application deployment. MLSysOps will design, implement
and evaluate a complete framework for autonomic end-to-end system management across the
full cloud-edge continuum. MLSysOps will employ a hierarchical agent-based AI architecture to
interface with the underlying resource management and application deployment/orchestration
mechanisms of the continuum. Adaptivity will be achieved through continual ML model learning
in conjunction with intelligent retraining concurrently to application execution, while openness
and extensibility will be supported through explainable ML methods and an API for pluggable
ML models. Flexible/efficient application execution on heterogeneous infrastructures and nodes
will be enabled through innovative portable container-based technology. Energy efficiency, per-
formance, low latency, efficient, resilient and trusted tier-less storage, cross-layer orchestration
including resource-constrained devices, resilience to imperfections of physical networks, trust
and security, are key elements of MLSysOps addressed using ML models. The framework archi-
tecture disassociates management from control and seamlessly interfaces with popular control
frameworks for different layers of the continuum. The framework will be evaluated using research
testbeds as well as two real-world application-specific testbeds in the domain of smart cities and
smart agriculture, which will also be used to collect the system-level data necessary to train and
validate the ML models, while realistic system simulators will be used to conduct scale-out experi-
ments. The MLSysOps consortium is a balanced blend of academic/research and industry/SME
partners, bringing together the necessary scientific and technological skills to ensure successful
implementation and impact.

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Inria Annual Report 2023

9.3.2 Other european programs/initiatives

Druid-Net

Participants:

Adriana Arteaga Arce, Carol Habid, Nathalie Mitton, Nina Santi.

Title: eDge computing ResoUrce allocatIon for Dynamic NETworks

Duration: May 2020 - September 2023

Inria contact: Nathalie Mitton

Summary: Following the NFV/SDN paradigm, DRUID-NET separates the flow of information into
control and data plane. At the lowest layer, the IoT-enabled applications are deployed, and the
generated workload (data flow) can be offloaded for further processing at the above EC layer, which
provides essential virtualized services. The DRUID-NET framework collects information (control
flow) about the status of the computing and network infrastructure at the EC level in order to
create workload-resource profiles, update the performance model for every application, and realize
the feedback control mechanism for the resource allocation and simultaneously implements a
resource-aware control strategy for the CPS to be controlled (control flow). This holistic approach
allows the application’s dynamical modelling taking into account various contextual information.
Furthermore, the controller co-design treats the resource allocation algorithms as application
components in the virtualized services.

NEWFOCUS

Participants:

Valeria Loscri.

Title: European network on future generation optical wireless communication technologies

Duration: September 2020 - September 2024

Inria contact: Valeria Loscri

Summary: The COST Action NEWFOCUS will propose truly radical solutions with the potential to impact
the design of future wireless networks. Particularly, NEWFOCUS aims to establish optical wireless
communications (OWC) as an efficient technology that can satisfy the demanding requirements of
backhaul and access network levels in beyond 5G networks. This also includes the use of hybrid
links that associate OWC with radiofrequency or wired/fiber-based technologies. Towards this
vision, NEWFOCUS will carry out a comprehensive research programme under two major pillars.
The first pillar is on the development of OWC-based solutions capable of delivering ubiquitous,
ultra-high-speed, low-power consumption, highly secure, and low-cost wireless access in diverse
application scenarios. The developed solutions will in particular support Internet-of-Things (IoT)
for smart environments with applications in vertical sectors. The second pillar concerns the devel-
opment of flexible and efficient backhaul/fronthaul OWC links with low latency and compatible
with access traffic growth.

BeingWise

Participants:

Valeria Loscri.

Title: Behavioral Next Generation in Wireless Networks for Cyber Security (BEiNG-WISE)

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Duration: 2023 - 2027

Action Chair and Scientific Holder: Valeria Loscri

Summary: The always-connected world we are living in, gives us an unprecedented plethora of new
advanced services and automated applications requiring, more and more, less human intervention
due to the increased integration of Machine Learning (ML), Artificial Intelligence (AI) approaches
and sophisticated emerging wireless technologies.

On the other side, this connected world opens new breaches and creates new potential vulner-
abilities for smart advanced cyber-attacks, namely attacks and offender relying on ML/AI and
advanced wireless technology integration, to make their attack more effective and less detectable.
If an increasing awareness by the users could help to contrast the security issues, it is not sufficient
against the new generation of cyber-attacks. In this context, a drastic paradigm shift, putting
human-being in the loop for the conception of novel and more effective cyber-security solutions,
must be considered.

Human-beings have a double role in the cyber-connected world: as potential offender and poten-
tial victim. The focus of BEiNG-WISE will be on how these different human-being features can be
combined with the advanced technological characteristics, in order to conceive non-conventional,
responsible by design, cyber-security solutions accounting for both these factors. In this complex
connected system, another fundamental aspect that needs to be accounted to, is the legal one,
related to the conception of solutions that can be effectively employed in the real world. Also, legal
aspects should be considered at the design stage. The Action relies on cross-domains expertise, ran-
ging from cybersecurity, wireless communication technology, data science, sociology, psychology
and law.

9.4 National initiatives
GoodFloow

Participants: Damien Wohwe Sambo, Nathalie Mitton.

Title: ADEME GoodFloow Project

Duration: October 2021 - September 2023

Coordinator: GoodFloow

Inria contact: Nathalie Mitton

Summary: The goal of this project, funded by ADEME, is to design a very energy efficient node to manage
reusable packaging in a more sustainable way by combining enhanced IA techniques, wake up
radio and multi MAC layers.

AutonomousPack

Participants: Damien Wohwe Sambo, Nathalie Mitton.

Title: ADEME Autonomous Pack Project

Duration: September 2023 - August 2026

Coordinator: GoodFloow

Inria contact: Nathalie Mitton

Summary: The goal of this project, funded by ADEME, is to design a very energy efficient node to manage
reusable packaging in a more sustainable way by combining enhanced IA techniques, wake up
radio and multi MAC layers.

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DEPOSIA

Participants:

Valeria Loscri.

Inria Annual Report 2023

Title: Detection and geolocation of an illegitimate electromagnetic source with AI

Duration: October 2021 - September 2024

Coordinator: Virginie Deniau

Inria contact: Valeria Loscri

Summary: The ANR project DEPOSIA focuses on the detection and geolocation of various radio fre-
quency signal sources in order to thwart attacks on connected systems and infrastructures. The
sources considered are elements which by their characteristics or their position, present an illi-
cit character and which threaten the people security or the infrastructures. For outdoor cases,
we consider drones flying over forbidden areas, telecommunication jammers, spoofing signal
transmitters or wireless connected sensors used to introduce false data in monitoring platforms.
For indoor cases, we also consider jamming or spoofing sources that can cause denial of service
within networks or infrastructures, or fake access points that aim to carry out man-in-the-middle
attacks to intercept information. In this proposal, the indoor and outdoor use cases are considered
separately in order to design monitoring infrastructures adapted to each case. For the outdoor
case, we consider a surveillance architecture that could join the already existing cellular or WLAN
communication infrastructures. In particular, with 5G technology and the higher employed fre-
quencies, cellular networks are evolving towards finer meshes and have interfaces with the core
network at each of their nodes. Thus, these interface points, equipped with receivers dedicated to
monitoring, could enable the routing of monitoring data to centralized platforms, feeding an Artifi-
cial Intelligence for analysis, anomaly detection and source geolocation. For the indoor case, we
consider a distributed monitoring architecture deployed within a building, based on SDR sensors
and a data centralization and synchronization network. In these two cases, we envisage an Artificial
Intelligence working on data evolving in three dimensions : time, space and direction, all for data
of different natures, namely those from the physical layer and the data link layer. Whether for
indoor or outdoor configurations, the algorithms that will constitute the Artificial Intelligence will
be based on learning approaches that will correspond to Machine Learning and Deep Learning
algorithms. These algorithms will deal with the problems of detecting attacks and locating illicit
sources. These algorithms will have to take into account: the evolutionary aspect brought by the
non-fixed character in time of the attacks and the non-fixed location aspect of the localization of
the source of the attack. A first Artificial Intelligence will be dedicated to data analysis and anomaly
detection, i.e., highlighting the suspicious nature of the data, and a second Artificial Intelligence will
be dedicated to extracting the location information of the attack source. Due to the multi-layered
nature of the data, model aggregation algorithms will be deployed in order to homogenize the
decision process.

ROAD-AI, common DEFI Inria and Cerema

Participants: Nathalie Mitton.

Title: Routes et ouvrages d’art Diversiformes, Augmentés et intégrés

Duration: July 2021 - June 2024

Inria contact: Nathalie Mitton

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Summary: Integrated management of infrastructure assets is an approach which aims at reconciling
long-term issues with short-term constraints and operational logic. The main objective is to enjoy
more sustainable, safer and more resilient transport infrastructure through effective, efficient
and responsible management. To achieve this, CEREMA and Inria are joining forces in this Inria
Challenge (DEFI) which main goals are to overcome scientific and technical barriers that lead to
the asset management of tomorrow for the benefit of road operators: (i) build a “digital twin” of
the road and its environment at the scale of a complete network; (ii) define “laws” of pavement
behavior; (iii) instrument system-wide bridges and tunnels and use the data in real time; (iv) define
methods for strategic planning of investments and maintenance.

PEPR

The FUN team is involved in PEPR Networks of the future (PC6 and PC7), PEPR Cloud (PC8) and PEPR

MobiDec (PC 3).

9.5 Regional initiatives

STIMULE CORTESE

Participants:

Valeria Loscri, Selma Yahia.

Title: CORTESE: Intelligent CO-existence of Communication Wireless Technologies for Secure and

Intelligent applications

Duration: January 2023 - December 2025

Inria contact: Valeria Loscri

Summary: This project led by the Inria Lille - Nord Europe center and in partnership with the Gustave
Eiffel University (UGE), the LAMIH (Université Polytechnique Hauts de France (UPHF)) aims at
the coexistence of different wireless communication technologies, in the vehicular context. The
objective is to advance in the search for methods based on sustainable Artificial Intelligence (AI)
which can automate the selection of the most relevant communication technology to improve
performance in terms of latency (i.e., of the order of 1 ms), reliability (i.e., of the order of 99.99% of
data delivered) in order to reduce the energy envelope of the communication system and guarantee
increased robustness in the face of cyber attacks. Given the high dynamicity of the environment,
the learning approaches developed must be capable of responding in real time. Particular attention
will be paid to the sustainability and security aspects of wireless communication networks. This
project is part of the field of embedded Artificial Intelligence and the new emerging sector of cyber
security for critical systems such as the vehicular context. With a clear experimental footprint, this
project will advance research in the Hauts-de-France region in 5G technology in a key sector such
as Intelligent Transport.

10 Dissemination

Participants:

Valeria Loscri, Nathalie Mitton.

10.1 Promoting scientific activities

General chair, scientific chair

• Valeria Loscri was organizer and chair of Social networking in Metaverse (SocMeta) Workshop,

Rome 2023

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Inria Annual Report 2023

• Valeria Loscri was co-organizer and chair of TRUSTNET DAY, Trust and Privacy in Networks,

Avignon, June 2023

• Valeria Loscri was co-organizer and chair of 1st Workshop on Underwater Communication, Access

and Networking (UCAN), in conjunction with ICC 2023

10.1.1 Scientific events: selection

Chair of conference program committees

• Valeria Loscri is Privacy and Security track chair at WF-IoT 2024, TPC co-chair of EWSN 2023, Sym-
posium Chair of Wireless Communications Symposium, Medium access control and Networking
Track chair at WCNC 2024 and Short Papers and Demo Session chair of WiMob 2023

• Nathalie Mitton was co-TPC chair of the 2023 GoodIt Special track chair and TPC co-chair of Algotel
2023. She is co-TPC chair of DCOSS 2024 and WiMob 2024 and Tuto and workshop co-chair of
EWSN 2024.

Member of the conference program committees

• Valeria Loscri has been a TPC member of IEEE Infocom 2023, Percom 2023, ESORICS 2023 and

2024, IEEE CSN 2023 and 2024.

• Nathalie Mitton has been a TPC member of Infocom 2023, DCOSS 2023, Percom 2023, Globecom

2023, and WCNC 2023.

10.1.2 Journal

Member of the editorial boards

• Valeria Loscri is Associate Editor of IEEE Transactions on Information Forensics and Security
(since 2022), IEEE Communications Survey and Tutorials (COMST, since 2020), Elsevier ComCom
(since 2021), Frontiers in Communications and Networks, ITU-FET Journal, IEEE Transactions on
Nanobioscience journal since 2017, of Elsevier Computer Networks journal since 2016, of Robotics
Software Design and Engineering of the International Journal of Advanced Robotic Systems since
2016, of Elsevier Journal of Networks and Computer Applications (JNCA) journal since 2016, of
Wiley Transactions Emerging Telecommunications Technologies since 2019.

• Nathalie Mitton is an editorial board member of Adhoc Networks since 2012, of IET-WSS since 2013,
of Wireless Communications and Mobile Computing since 2016, of Journal of Interconnection
Networks since 2021.

10.1.3 Invited talks

• Valeria Loscri was invited speaker at workshop Inria-CISPA, Paris

• Valeria Loscri was invited speaker at 8th Franco-Japanese Cybersecurity workshop, Bordeaux

• Valeria Loscri was invited keynote speaker at ENAC - Toulouse to deliver a talk on How Machine

Learning is changing the Cybersecurity landscape in Wireless Communication Networks

• Valeria Loscri was invited keynote speaker at ENAC - Toulouse to deliver a talk on How Machine

Learning is changing the Cybersecurity landscape in Wireless Communication Networks

• Valeria Loscri was invited keynote speaker on Machine Learning and Visible Light Communication

at the Journées Scientifiques URSI - France

• Valeria Loscri was invited keynote speaker at the PhD Day - INSA Lyon, with a talk on Unconven-

tional Wireless Communication Technologies

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• Valeria Loscri invited speaker at Journée Sécurité CRISTAL, with a talk on How Machine Learning is

changing the Cybersecurity landscape in Wireless Communication Networks

• Nathalie Mitton was invited keynote at November 2023 CONNECT THEM ALL session.

10.1.4 Scientific expertise

• Valeria Loscri has been appointed as Evaluator Expert for Horizon Europe KDT-JU Program and

Horizon Europe 6G SNS-JU Program,

• Valeria Loscri is FWO expert panel member for the PhD fellowship-Fundamental Research and for

the Postdoc fellowship-Fundamental Research.

• Nathalie Mitton has been appointed as scientific expert to evaluate projects submitted to ANR,

South Africa’s National Research Foundation (NRF), NSERC (Canada) and NSC (Poland).

• Nathalie Mitton is an external expert of scientific board for Inrae, IRIT lab and ESISAR.

10.2 Teaching - Supervision - Juries

10.2.1 Teaching

• Master: Valeria Loscri, Objets Communicants, 24h (Mineure Habitat Intelligent), Ecole des Mines

de Douai, France

• Master: Nathalie Mitton, Wireless networks, 16h eqTD (Master TC), Université de Lille, France

• Master: Damien Wohwe Sambo, Wireless sensor networks, 16h eqTD (Master IdO), Université de

Lille, France

• Master: Adriana Arteaga Arce and Hazem Chaabi, Smart objects, 10h CM + 12h TP, Ecole Centrale

de Lille, France

• Master: Adriana Arteaga Arce and Hazem Chaabi, Industrial Internet of Things, 10h CM, Ecole

Centrale de Lille, France

• Master: Damien Wohwe Sambo, Industrial to Internet of Things, 4h Cours + 12h TP, Ecole Centrale

de Lille, France

• Master: Damien Wohwe Sambo, Wireless sensor networks, 12h eqTD (Master ROC), IMT, France

10.2.2 Supervision

• PhD defended:

– Nina Santi, adaptive and dynamic edge gateways IoT-oriented deployments, Université de

Lille, 2020-2023, defended on December 19, Nathalie Mitton

• PhD in progress:

– Aymen Bouferroum, vulnerability detection, trust and authentication methods applied to
multi-technology communication in Industrial IoT (IIoT), Université de Lille, 2023-2026,
Valeria Loscri

– Selina Cheggour, Cell-free approaches in wireless networks, Université de Lille, 2023-2026,

Valeria Loscri

– Marwa Slimene, Blockchain-based security and audit for ioT and V2X communications,

Université de Lille, 2023-2026, Nathalie Mitton

– Jiali Xu, anomaly and attack detection in intelligent, deep systems with heterogeneous, repro-

grammable nodes, Université de Lille, 2023-2026, Valeria Loscri

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Inria Annual Report 2023

– Hazem Chaabi, Adaptive deployment of a distributed wireless monitoring network and edge

services using a fleet of wireless robots, Université de Lille, 2022-2025, Nathalie Mitton

– Ildi Alla, Monitoring for detection and localisation of cyber attacks in wireless networks,

Université de Lille, 2022-2025,Valeria Loscri

– Jana Koteich, Context aware opportunistic forwarding strategy, Université de Lille, 2021-2024,

Nathalie Mitton

10.2.3 Juries

PhD committees:

• Valeria Loscri is/was member of the following PhD thesis committees:

– Ali Haj-Hassan, University of Mons, examiner and secretary.

– Michaël Mahamat, University of Compiegne, examiner.

– Abhishek Djeachandrane, University of Paris Est, reviewer.

– Shuo Li, Centrale Supélec, reviewer

– Firmin Kateu, University of Toulouse, reviewer

– Farzad Veisi, University of Strasbourg, reviewer.

– Khaled Abid, University of Compiegne, reviewer.

– Alessandro Visentin, University of Padova, reviewer.

– Chaima Zoghlami, Universiy of Toulouse, reviewer.

– Chaimaa BOUDAGDIGUE, Univ. of Avignon, reviewer.

– Sana BENHAMAID, Univ. of Compiegne, reviewer;

– Bruno CHIANCA, ENAC, Toulouse, reviewer;

• Nathalie Mitton is/was member of the following PhD thesis committees:

– Debashisha Mishra, Lorraine university, chair

– Vishaka Basnayake, UTBM, chair

– Maysaa Khalil, UTT

– Berat Senet, Sorbonne University, reviewer

– Ichrak Mokhtari, INSA Lyon, reviewer

– Ludovic Javet, UVSQ, chair

– Hugo Hadjur, ENS Lyon, reviewer

– Jad Bassil, Univ. Bourgogne, chair

– Razanne Abu-Aisheh, Sorbonne Université, chair and reviewer

– Hadi Yakan, UVSQ, chair

– Driss Aouladhaj, UGE, chair

– Olivier Lourme, Univ. Lille

Researcher selection committees:

• Valeria Loscri is/was member of the following selection committees:

– Inria Junior Research (CR) committee for Inria Lyon

– Assistant professor: Université Côte d’Azur, Université de Toulouse

– National Secondment Committee Inria

• Nathalie Mitton was member of the following selection committees:

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– Inria researcher: vice-chair of the junior researcher committee (CR) for Inria Lille and member

of Senior researcher committee (DR2)

– Professor: Universités de Lorraine.

– Assistant professor: Université d’Annecy, IMT Lille Nord Europe, Sorbonne University, Uni-

versité Polytechnique des Hautes de France

– CPJ : INSA Lyon, Inria Lille

10.3 Internal or external Inria responsibilities

• Nathalie Mitton

– is Deputy Scientific delegate for Lille Inria center

– is member of the QVT (Quality of life at work) committee

– is a member of the Bureau des Comités de Projets of Lille Inria center.

– is a member of the evaluation committee of Inria.

• Valeria Loscri

– is Scientific International Relation Responsible for Inria Lille.

– is Staff Representative (substitute)

11 Scientific production

11.1 Publications of the year

International journals

[1] R. Giuliano, A. M. Vegni, V. Loscrì, E. Innocenti, A. Vizzarri and F. Mazzenga. ‘MuSLi: a Multi Sensor
LiDAR Detection for C-V2X Networks’. In: Computer Networks (Jan. 2023). URL: https://hal.sci
ence/hal-03907360.

[2]

J. Koteich, C. Salim and N. Mitton. ‘Image processing based data reduction technique in WVSN
for smart agriculture’. In: Computing (25th July 2023). DOI: 10.1007/s00607-023-01198-2. URL:
https://hal.science/hal-04173213.

[3] V. Loscri, C. Rizza, A. Benslimane, A. M. Vegni, E. Innocenti and R. Giuliano. ‘BEST-RIM: a mmWave
Beam Steering Approach based on Computer Vision-enhanced Reconfigurable Intelligent Metasur-
faces’. In: IEEE Transactions on Vehicular Technology (2023). URL: https://hal.science/hal-0
3955383.

[4] C. Marche, V. Loscri and M. Nitti. ‘A Channel Selection Model based on Trust Metrics for Wireless
Communications’. In: IEEE Transactions on Network and Service Management (May 2023), pp. 1–1.
DOI: 10.1109/TNSM.2023.3277578. URL: https://hal.science/hal-04101037.

[5] A. Petroni, A. Costanzo, V. Loscrì and M. Biagi. ‘A Novel Optical Wireless Modulation exploiting
Time, Frequency and Amplitude divisions enabling Link and Illumination Reliability’. In: IEEE
Transactions on Wireless Communications (July 2023). DOI: 10.1109/TWC.2023.3285822. URL:
https://hal.science/hal-04115865.

[6] E. Staddon, V. Loscri and N. Mitton. ‘A consensus-based approach to reputational routing in multi-
hop networks’. In: ITU Journal on Future and Evolving Technologies (2023). URL: https://inria
.hal.science/hal-03969218.

[7] A. M. Vegni, C. Leoni, V. Loscri and A. Benslimane. ‘A Reputation-based Trustworthiness Concept
for Wireless Networking in Vehicular Social Networks’. In: IEEE Communications Magazine (Sept.
2023). URL: https://hal.science/hal-04256151.

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Inria Annual Report 2023

[8] B. Wang, J. Zheng, N. Mitton and C. Li. ‘InP-CRS: an Intra-Platoon Cooperative Resource Selection
Scheme for C-V2X Networks’. In: IEEE Communications Letters (Oct. 2023). URL: https://inria
.hal.science/hal-04233626.

[9] D. Wohwe Sambo, J. Dede, N. Mitton and A. Förster. ‘FuzDeMa: A portable Fuzzy-based Decision-
Making tool for reliable communication in Wireless Underground Sensor Networks’. In: ITU Journal
on Future and Evolving Technologies 4.3 (2023), pp. 419–433. DOI: 10.52953/IXIP2995. URL: http
s://hal.science/hal-04197809.

[10] C. Zidi, P. Sondi, N. Mitton, M. Wahl and A. Meddahi. ‘Review and Perspectives on the Audit of
Vehicle-to-Everything Communications’. In: IEEE Access 11 (9th Aug. 2023), pp. 81623–81645. DOI:
10.1109/ACCESS.2023.3301182. URL: https://hal.science/hal-04181120.

International peer-reviewed conferences

[11] E. Bout, V. Bout, A. Brighente, M. Conti and V. Loscri. ‘Evaluation of Channel Hopping Strategies
Against Smart Jamming Attacks’. In: IEEE International Conference on Communications. IEEE
ICC 2023 - IEEE International Conference on Communications. Rome, Italy, 28th May 2023. URL:
https://hal.science/hal-03950904.

[12] N. E. H. Djidi, D. Wohwe Sambo, M. Gautier, O. Berder and N. Mitton. ‘WUBBLE: Energy Efficient
BLE Neighborhood Discovery Leveraging Wake-up Radio’. In: Algorithmics of Wireless Networks,
19th International Symposium on Algorithmics of Wireless Networks (ALGOWIN 2023). Algorithmics
of Wireless Networks, 19th International Symposium on Algorithmics of Wireless Networks (AL-
GOWIN 2023). Amsterdam, Netherlands, 1st Aug. 2023. URL: https://hal.science/hal-04170
115.

[13] B. Foubert, C. Salim and N. Mitton. ‘Chained estimation for data reduction-driven routing in
wireless sensor networks’. In: WiMob 2023 - 19th International Workshop on Selected Topics in
Wireless and Mobile computing. WiMob 2023 - 19th International Workshop on Selected Topics in
Wireless and Mobile computing. Montreal, Canada, 21st June 2023. URL: https://hal.univ-gre
noble-alpes.fr/hal-04098170.

[14]

J. Koteich and N. Mitton. ‘Machine Learning Approach for Mobility Context Classification using
Radio Beacons’. In: Proc of 31st International Symposium on the Modeling, Analysis, and Simula-
tion of Computerand Telecommunication Systems. MASCOTS2023 IEEE. New York, United States,
16th Oct. 2023. URL: https://hal.science/hal-04208815.

[15] F.-X. Molina, V. Roca, R. Dagher, E. Baccelli, N. Mitton, A. Boutet and M. Cunche. ‘PEPPER: Precise
Privacy-Preserving Contact Tracing with Cheap, BLE/UWB Capable Tokens’. In: WoWMoM 2023
- 24th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks.
Boston, United States: IEEE, 12th June 2023, pp. 1–10. URL: https://inria.hal.science/hal-
04064415.

[16] C. Rizza and V. Loscri. ‘AIRISC -A mmWave Angle-Insensitive Reconfigurable Intelligent Surface
Communication System’. In: International Conference on Embedded Wireless Systems and Net-
works (EWSN). Rende, Italy, 25th Sept. 2023. URL: https://hal.science/hal-04162929.

[17] B. Wang, N. Mitton and J. Zheng. ‘PreZcast: A Preferred-Zone Based Broadcast Protocol for Urban
Areas of VANETs’. In: IEEE ICC 2023 - IEEE International Conference on Communications. Roma,
Italy, 28th May 2023. URL: https://inria.hal.science/hal-03966986.

National peer-reviewed Conferences

[18]

J. Koteich and N. Mitton. ‘PILOT Dataset: A Collection of Multi-Communication Technologies
in Different Mobility Contexts’. In: CoRes 2023 - 8th Francophone Meeting on Protocol Design,
Performance Evaluation and Communication Network Experimentation. CoRes 2023 - 8th Fran-
cophone Meeting on Protocol Design, Performance Evaluation and Communication Network
Experimentation. Cargese, France, 22nd May 2023. URL: https://hal.science/hal-04090609.

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11.2 Cited publications

[19] N. Santi, R. Grünblatt, B. Foubert, A. Hameed, J. Violos, A. Leivadeas and N. Mitton. ‘Automated
and Reproducible Application Traces Generation for IoT Applications’. In: Q2SWinet 2021 - 17th
ACM Symposium on QoS and Security for Wireless and Mobile Networks. Alicante, Spain: ACM, Nov.
2021, pp. 1–8. DOI: 10.1145/3479242.3487321. URL: https://hal.science/hal-03390693.
<scratchpad>
- Main topic: Research Centre FUN (Inria Centre at the University of Lille)
- Key points:
  - Research focus: Networks, Systems and Services, Distributed Computing
  - Project FUN aims to address challenges of wireless devices and their data
  - Three research axes: Frugality and opportunism, Security, Interconnectivity
  - Application domains: Smart Agriculture, Vehicular networks, Smart infrastructures, Logistic and traceability
  - Partnerships and cooperations: International initiatives, European programs/initiatives, National initiatives
- Structure: Document is divided into sections (e.g., Project-Team, Activity Report, Research Program)
- Potential artifacts to ignore: HTML tags, links, and other web-related elements
</scratchpad>

<final_summary>
The FUN project, part of the Inria Centre at the University of Lille, focuses on addressing challenges of wireless devices and their data. The research centre is divided into three main axes: Frugality and opportunism, Security, and Interconnectivity. The project aims to improve the efficiency and security of wireless networks, particularly in application domains such as smart agriculture, vehicular networks, and smart infrastructures. FUN also collaborates with international partners and European programs to advance the field of wireless communication technologies.</final_summary>
The FUN project, part of the Inria Centre at the University of Lille, focuses on addressing challenges of wireless devices and their data. The research centre is divided into three main axes: Frugality and opportunism, Security, and Interconnectivity. The project aims to improve the efficiency and security of wireless networks, particularly in application domains such as smart agriculture, vehicular networks, and smart infrastructures. FUN also collaborates with international partners and European programs to advance the field of wireless communication technologies.