7.1.1 ACQUAmobile

• Name:
  Application for prediCting Quality of User Experience at Internet Access
• Keywords:
  Android, Internet access, Performance measure, Quality of Experience
• Scientific Description:

  ACQUA is an Application for prediCting QUality of Experience (QoE) at Internet Access. It is developed by the Diana team at Inria Sophia Antipolis – Méditerranée and was supported by Inria under the ADT ACQUA grant. The scientific project around ACQUA is supported by Inria Project Lab BetterNet and the French National Project ANR BottleNet. The project also got the approval of Inria COERLE and French CNIL for the part on experimentation with real users. ACQUA presents a new way for the evaluation of the performance of Internet access. Starting from network-level measurements as the ones we often do today (bandwidth, delay, loss rates, jitter, etc), ACQUA targets the estimated Quality of Experience (QoE) related to the different applications of interest to the user without the need to run them (e.g., estimated Skype quality, estimated video streaming quality).

  The ACQUA Android application is supposed to be on one hand the reference application for QoE forecasting and troubleshooting for end users at their Internet access, and on the other hand, the feedback channel that allows end users to report to us (if they are willing) on their experience together with the corresponding network measurements so as to help us calibrating better and more realistic models. For this calibration, we are currently performing extensive, efficient and automatic measurements in the laboratory, we will count on end users to help us completing this dataset with further applications and more realistic network and user conditions.

  ACQUA is mainly meant for end users, but it is also of interest to (mobile) network operators and to content providers to estimate the QoE of their customers and their networks without each time having to run expensive application-level traffic and to involve real users.

• Functional Description:

  An application in ACQUA is a function, or a model, that links the network-level and device-level measurements to the expected Quality of Experience. Supervised machine learning techniques are used to establish such link between measurements both at the network level and the device level, and estimations of the Quality of Experience for different Internet applications. The required data for such learning can be obtained either by controlled experiments as we did in a prior work on Skype and YouTube Quality of Experience, or by soliciting the crowd (i.e. crowdsourcing) for combinations (i.e. tuples) of network- and application-level measurements and corresponding user-level Quality of Experience. Our current work is concentrating on using the ACQUA principle in the estimation and prediction of the Quality of Experience for main user’s applications. We refer to the web site of the project for further details.

  Assessment: Audience = 3, Software Originality = 4, Software Maturity = 3, Evolution and Maintenance = 3, Software Distribution and Licensing = 5.

• URL:
  http://­project.­inria.­fr/­acqua/
• Authors:
  Thierry Spetebroot, Chadi Barakat
• Contact:
  Chadi Barakat

7.1.2 ElectroSmart

• Keywords:
  Crowd-sourcing, UMTS, GSM, Bluetooth, Wi-Fi, 4G, 3G, 2G, Electromagnetic waves, Android, LTE
• Functional Description:

  The Internet and new devices such as smartphones have changed fundamentally the way people communicate, but this technological revolution comes at the price of a higher exposition of the general population to microwave electromagnetic fields (EMF). This exposition is a concern for health agencies and epidemiologists who want to understand the impact of such an exposition on health, for the general public who wants a higher transparency on its exposition and the health hazard it might represent, but also for cellular operators and regulation authorities who want to improve the cellular coverage while limiting the exposition, and for computer scientists who want to better understand the network connectivity in order to optimize communication protocols. Despite the fundamental importance to understand the exposition of the general public to EMF, it is poorly understood because of the formidable difficulty to measure, model, and analyze this exposition.

  The goal of the ElectroSmart project is to develop the instrument, methods, and models to compute the exposition of the general public to microwave electromagnetic fields used by wireless protocols and infrastructures such as Wi-Fi, Bluetooth, or cellular. Using a pluri-disciplinary approach combining crowd-based measurements, in-lab experiments, and modeling using sparse and noisy data, we address challenges such as designing and implementing a measuring instrument leveraging on crowd-based measurements from mobile devices such as smartphones, modeling the exposition of the general public to EMF to compute the most accurate estimation of the exposition, and analyzing the evolution of the exposition to EMF with time. This technological breakthrough will have scientific, technical, and societal applications, notably on public health politics, by providing the scientific community and potential users with a unique measuring instrument, methods, and models to exploit the invaluable data gathered by the instrument.

  This project is supported by the UCN@Sophia Labex in 2016/2017/2018 (funding the engineer Mondi Ravi), by an Inria ADT (funding the engineer Abdelhakim Akodadi) 2017/2018, by and Inria ATT (funding the business developer David Migliacci) in 2017/2018, and by the academy 1 of UCAJedi (funding a Ph.D. student Yanis Boussad) 2017/2021.

  In August 2016, we released the first stable public release of ElectroSmart. On the 30th December 2021 the app has been downloaded 1.1 million time, we have 200 000 active users and a score of 4,5/5 on Google Play. We collected 13 billions measurements in 150 countries.

  Assessment: A-5, SO-4, SM-4, EM-3-up4, SDL-1

• URL:
  https://­electrosmart.­app
• Contact:
  Arnaud Legout
• Participants:
  Arnaud Legout, Mondi Ravi

7.1.3 nepi-ng

• Keywords:
  Wireless network, Experimentation
• Functional Description:

  In the specific context of R2lab, we have created a tool suite for orchestrating network experiments, that for historical reasons we refer to collectively as nepi-ng, for NEPI new generation. An umbrella website is available at https://nepi-ng.inria.fr/.

  At this point, nepi-ng has a much smaller scope than its NEPI ancestor used to have, in that it only supports remote control of network experiments over ssh. As a matter of fact, in practice, this is the only access mechanism that we need to have for running experiments on both R2lab, and PlanetLab Europe.

  The design of nepi-ng of course is modular, so that it will be perfectly possible to add other control mechanisms to this core if and when it becomes necessary.

  • asynciojobs:
    • URL: http://­asynciojobs.­readthedocs.­io/­en/­latest/
    • Version: asynciojobs v0.5.4
    • Keywords: networking experimentation, orchestration
    • License: CC BY-SA 4.0
    • Type of human computer interaction: python library
    • OS/Middleware: Linux
    • Required library or software: python-3.5 / asyncio
    • Programming language: python3
  • apssh:
    • URL: http://­apssh.­readthedocs.­io/­en/­latest/
    • Version: apssh v0.7.1
    • Keywords: networking experimentation, orchestration
    • License: CC BY-SA 4.0
    • Type of human computer interaction: python library
    • OS/Middleware: Linux
    • Required library or software: python-3.5 / asyncio
    • Programming language: python3
• URL:
  http://­nepi-ng.­inria.­fr
• Contact:
  Thierry Parmentelat

7.1.4 Distrinet

• Name:
  Distrinet
• Keywords:
  SDN, Emulation, Large-scale Emulators, Network simulator
• Scientific Description:

  Networks have become complex systems that combine various concepts, techniques, and technologies. As a consequence, modelling or simulating them now is extremely complicated and researchers massively resort to prototyping techniques. Mininet is the most popular tool when it comes to evaluate SDN propositions. Mininet allows to emulate SDN networks on a single computer but shows its limitations with resource intensive experiments as the emulating host may become overloaded. To tackle this issue, we propose Distrinet, a distributed implementation of Mininet over multiple hosts, based on LXD/LXC, Ansible, and VXLAN tunnels. Distrinet uses the same API than Mininet, meaning that it is compatible with Mininet programs. It is generic and can deploy experiments on Linux clusters (e.g., Grid’5000), as well as on the Amazon EC2 cloud platform.

  Assessment: A5, SO3, SM2, EM2-down, SDL4

• Functional Description:
  Distrinet is an extension of Mininet that relies on LXC to be distributed in the cloud, and particularly in Amazon. The extension has been designed to be fully compatible with Mininet. As using Distrinet potentially involves the collaboration of multiple machines we focused on guaranteeing the correctness (in a sense that results are trustworthy) of simulations when running on multiple machines. To speedup deployments, loading and unloading operations have been parallelised with asynchronous calls. The pool of machines used for simulations is automatically provisioned thanks to Ansible.
• Release Contributions:
  First release
• URL:
  https://­distrinet-emu.­github.­io
• Publication:
  hal-03000617v1
• Contact:
  Walid Dabbous
• Participants:
  Damien Saucez, Giuseppe Di Lena, Andrea Tomassilli, Frédéric Giroire, Thierry Turletti
• Partner:
  Orange Labs

7.1.5 OMNET-TSN

• Name:
  OMNET-TSN
• Keywords:
  Real time, Network simulator
• Functional Description:

  Time Sensitive Networking (TSN) aims at providing real time capabilities to Ethernet networks. To achieve this goal, the 2018 revision of the IEEE802.1Q standard (i.e., IEEE802.1Q-2018) provides the ability to define transmission selection algorithms for queues in IEE802.1Q Ethernet switches.

  We are developing an IEEE802.1Q-2018 simulation module for OMNeT++. The usual way to implement a simulation module is to abstract the components to be simulated and leverage the simulator functionalities. As a result, simulations can run very efficiently and scale well. The drawback is that the code base is only understandable by well trained developers and hardly understandable by engineers.

  With our implementation we decided to make a direct transpose of the normative documents into the simulator such that anyone that reads the standards can read the code and adapt it if needed. This approach makes simulations runs last much longer than if they code were optimized for simulations but the major advantage is that engineers used to read standards and evaluate appliances provided by third parties can use it with minimal training.

  The simulator code is implemented in C++ in Omnest (the commercial version of OMNeT++). As in most industrial environments it is extremely complex to install non corporate software, we implemented a front-end in javascript with the REACT framework. As a consequence, it is possible to install and run the simulation tool on a dedicated machine/VM/container and to drive simulations from any workstation solely by using a web browser.

• Release Contributions:
   

  • Multiple bug fixes in CBS
  • CBS as a transmission selection algorithm instead of a transmission queue
  • Complete tutorials for users
  • Full code documentation for developper
  • Delete message from QeuingFrame::handleMessage after it has been cloned to reduce memory footprint for large experiments
  • Includes std algorithm library to compile on Linux std::set_intersection
  • Add processing delay simulation
  • Automated testing with docker
• URL:
  https://­github.­com/­dsaucez/
• Contact:
  Damien Saucez

7.2.1 Reproducible research Lab - R2lab

Scientific work around network protocols and related software stacks requires experiments, hence experimental conditions, to be reproducible. This is a particularly challenging requirement in the wireless networking area, where characteristics of wireless channels are known to be variable, unpredictable and hardly controllable.

The R2lab wireless testbed was designed with reproducibility as its central characteristics; it is built around an isolated and anechoic chamber, featuring RF absorbers that prevent radio waves reflections, and a Faraday cage blocking external interferences. R2lab thus provides an ideal environment for running reproducible wireless experiments.

R2lab has been operated since December 2015, in the context of the FIT (Future Internet of Things) Equipment of Excellence project, and as such, it is now federated with the other testbeds that are part of the FIT initiative. As of early 2019, it has been also federated within the Fed4Fire initiative.

Available toolsets, both hardware and software, are mostly stable apart from low noise marginal deployment of new kinds of radio devices, that now encompass among 5G and LoRa, among others. Our focus at this point of the project is to leverage our initial technical and financial investment, and to produce scientific work around reproducibility, particularly from a methodological standpoint, as illustrated by various publications listed in the R2lab web site.

Worth being mentioned as well, as part of a partnership with the OpenAirInterface initiative, R2lab is used on a daily basis for system-wide regression tests of the OAI stack, which in return allows us to offer up-to-date images for running OAI-based experiments. Emphasis has been put lately on offering tools that leverage kubernetes as the swiss-knife for orchestrating the deployment of a complete 5G infrastructure as an elastic set of microservices.

In 2021, the management tools on R2lab were extended to support running docker images, in addition to the historic, metal-based image format (.ndz). This allows experimenters to build their images using mainstream tools and base images. Thanks to that, we can now expose the latest OAI code as R2lab-ready docker images, both for EPC and RAN.

Access to R2lab is open 24/7. R2lab is used by more than 150 users half of them from France and the other half from all over the world (Australia, Belgium, Brazil, Canada, Chile, Spain Finland, Germany, India, Indonesia, Italy, Japan, Luxembourg, Netherlands Norway, Tunisia, Turkey, UK, US, Vietnam, etc.) to evaluate a wide range of wireless networking scenarios in realistic and reproducible environment. Examples are deployment of a 4G network in less than 4 minutes (demonstrated at Sigcomm 2017 6), Mininet-WiFi calibration (demon paper at Sigcomm 2016  34), Orientation Estimation, Joint range extension and localization, Mobile Edge Cloud scenarios, Ad-hoc routing protocols comparison, side channel analysis (CCS), QoE for Internet Video, Mobile video streaming leveraging in-network functions, Reproducible 5G network automation with Kube5G, Fidelity Monitoring of Distributed Network Emulation, Cross-layer Loss Discrimination Algorithms for MEC in 4G networks, Reproducing the OpenRF experiment (Reproducibility workshop, Sigcomm  36). For more details see R2lab home page. As the future of R2lab, there are wider plans to rebuild the Inria Sophia facility more or less from scratch. As R2lab is still used by the community, the plan is to include R2lab as an addition the Sophia Node that is currently being developed in collaboration with the OpenAirInterface consortium at Eurecom.

7.2.2 SophiaNode: an open programmable 5G platform

Our project-team started in collaboration with Eurecom to deploy an open programmable platform to test 5G services. This year, R2lab was connected to sister site at Eurecom with 600 Gbps fibers forming together the so-called SophiaNode of the ESFRI SLICES-RI project. We plan to enrich R2lab with 5G professional radio units and with Kubernetes clustered server farm, and therefore to provide an experimental environment to test with open source (OAI, SrsLTE) software and some commercially licensed software (e.g. Amarisoft) for 5G/6G networks supporting for example scenarios with disaggregated 5G networks elements. Initial deployment has already started in 2021 and will continue in 2022.

7.2.3 Network simulator for aircrafts

• Keywords: network, simulation, real-time
• Functional Description: In collaboration with Safran Electrical and Power we produced a network design tool for aircrafts. This tool simulates aircraft networks. The tool is about 10,000 lines of code, out of which we produced 2,000.
• Assessment: A-2up,SO-3,SM-2up,EM-4,SDL-3,OC-DA-CD-TPM
• Licence: confidential
• URL: confidential
• Contact: Damien Saucez

8.1.1 Leveraging Website Popularity Differences to Identify Performance Anomalies

Participants: Giulio Grassi, Chadi Barakat.

This study was funded by Inria within IPL BetterNet and was performed in collaboration with the EPI MIMOVE of Inria Paris and the Department of Computer Science of Boston University. Its focus is on the detection of performance anomalies across websites with a large span of popularities. In fact, Web performance anomalies (e.g. time periods when metrics like page load time are abnormally high) have significant impact on user experience and revenue of web service providers. Existing methods to automatically detect web performance anomalies focus on popular websites (e.g. with tens of thousands of visits per minute). However, across a more representative set of websites, passive measurement volume varies enormously, and some sites will only have small numbers of measurements per hour. Low rates of measurement creates gaps and noise that prevent the use of existing methods. This study develops WMF, a web performance anomaly detection method applicable across a range of websites with highly variable measurement volume. To demonstrate our method, we leverage data from a website monitoring company partner of the IPL BetterNet, which allows us to leverage cross-site measurements. WMF uses matrix factorization to mine patterns that emerge from a subset of the websites to "fill in" missing data on other websites. Our validation using both a controlled website and synthetic anomalies shows that WMF's F1-score is more than double that of the state-of-the-art method. We then apply WMF to three months of web performance measurements to shed light on performance anomalies across a variety of 125 small to medium websites. The results of this work were presented at the IEEE INFOCOM 2021 conference 24.

8.1.2 Unveiling the end-user viewport resolution from encrypted video traces

Participants: Othmane Belmoukadam, Chadi Barakat.

Video streaming is without doubt the most requested Internet service, and main source of pressure on the Internet infrastructure. At the same time, users are no longer satisfied by the Internet's best effort service, instead, they expect a seamless service of high quality from the side of the network. As result, Internet Service Providers (ISP) engineer their traffic so as to improve their end-users' experience and avoid economic losses. Content providers from their side, and to enforce customers privacy, have shifted towards end-to-end encryption (e.g., TLS/SSL). Video streaming relies on the dynamic adaptive streaming over HTTP protocol (DASH) which takes into consideration the underlying network conditions (e.g., delay, loss rate, and throughput) and the viewport capacity (e.g., screen resolution) to improve the experience of the end user in the limit of the available network resources. In this work, we propose an experimental framework able to infer fine-grained video flow information such as chunk sizes from encrypted YouTube video traces. We also present a novel technique to separate video and audio chunks from encrypted traces based on Gaussian Mixture Models (GMM). Then, we leverage our dataset to train models able to predict the class of viewport (either SD or HD) per video session with an average 92% accuracy and 85% F1-score. The prediction of the exact viewport resolution is also possible but shows a lower accuracy than the viewport class. This work fits within the PhD thesis of Othmane Belmoukadam 26 and is published in IEEE Transactions on Network and Service Management 11.

8.1.3 Longitudinal Study of Exposure to Radio Frequencies at Population Scale

Participants: Yanis Boussad, Arnaud Legout, Walid Dabbous.

Evaluating population-scale exposure to the radio frequencies (RF) used in wireless telecommunication technologies is important for conducting sound epidemiological studies on the health impacts of these RF. Numerous studies have reported population exposure, but have used very small population samples. In this context, the real exposure of the population to RF remains subject to controversy. Here, to the best of our knowledge, we report the largest crowd-based measurement of population exposure to RF produced by cellular antennas, Wi-Fi access points, and Bluetooth devices for 254,410 unique users in 13 countries from January 2017 to December 2020. All measurements were obtained from the ElectroSmart Android app, and we applied a thorough methodology to clean and consolidate the measurements. We show that total exposure has been multiplied by 2.3 in the four-year period considered, with Wi-Fi as the largest contributor. The cellular exposure levels are orders of magnitude lower than the regulation limits and not significantly impacted by national regulation policies. Therefore, the mere comparison of exposure levels to regulation limits is a poor way to describe the real evolution of exposure. The population tends to be more exposed at home; for half of the study subjects, personal Wi-Fi routers and Bluetooth devices contributed to more than 50% of their total exposure. We make our dataset publicly available to provide a starting point for sound epidemiological studies on the health impacts of RF, and for other types of studies interested in population exposure to RF or the usage of wireless communication technologies. This work is under submission 29.

8.1.4 Evaluating smartphone performance for cellular power measurement

Participants: Yanis Boussad, Mondi Ravi, Arnaud Legout, Walid Dabbous.

Smartphones are affordable devices nowadays, capable of embedding a large variety of sensors such as magnetometers or orientation sensors, but also the hardware needed to connect them to most wireless communication technologies such as Wi-Fi, Bluetooth, or cellular networks. Therefore, they are handy devices able to perform received signal strength indicator RSSI measurements for a wide variety of applications such as cellular coverage maps, indoor localization, or proximity tracking. However, to the best of our knowledge, the accuracy of such measurements has never been rigorously assessed. The goals of this article are to assess the accuracy of the RSSI measurements made with a commercial off-the-shelf smartphone in a variety of conditions and how possible inaccuracies can be corrected. We primarily focus on the long-term evolution (LTE) RSSI, but we also extend our results to the Bluetooth RSSI. In this article, we build a controlled experimental setup based on commodity hardware and on open-source software. We evaluate the granularity and limitations of the Android application programming interface that returns the RSSI. We explore how reliable the measurements in a controlled environment with a mono-polarized antenna are. We show that the orientation of the smartphone, the position or orientation of the source, and the transmission power have a significant impact on the accuracy of the measurements. We introduce several correction techniques based on radiation matrix manipulations and on machine learning in order to improve measurement accuracy to less than 5 dB Root Mean Square Error, when compared to a professional equipment. We also explore the reliability of measurements made in an outdoor realistic environment. We show that although transmission diversity available in LTE base stations significantly improves the measured RSSI regardless of the smartphone orientation, the Bluetooth RSSI remains largely sensitive to the smartphone orientation. The complete work is published in Transactions on Instrumentation and Measurements 13.

8.1.5 Did I delete my cookies? Cookies respawning with browser fingerprinting

Participants: Imane Fouad, Arnaud Legout.

Stateful and stateless web tracking gathered much attention in the last decade, however they were always measured separately. To the best of our knowledge, our study is the first to detect and measure cookie respawning with browser and machine fingerprinting. We develop a detection methodology that allows us to detect cookies dependency on browser and machine features. Our results show that 1,150 out of the top 30, 000 Alexa websites deploy this tracking mechanism. We further uncover how domains collaborate to respawn cookies through fingerprinting. We find out that this technique can be used to track users across websites even when third-party cookies are deprecated. Together with a legal scholar, we conclude that cookie respawning with browser fingerprinting lacks legal interpretation under the GDPR and the ePrivacy directive, but its use in practice may breach them, thus subjecting it to fines up to 20 million. This work is under submission 31. This study was performed in collaboration with Nataliia Bielova from the EPI PRIVATICS of Inria Grenoble Rhône-Alpes.

8.1.6 In-Depth Technical and Legal Analysis of Tracking on Health Related Websites with ERNIE Extension

Participants: Imane Fouad, Yanis Boussad, Arnaud Legout.

Searching the Web to find doctors and make appointments online is a common practice nowadays. However, simply visiting a doctors website might disclose health related information. As the GDPR only allows processing of health data with explicit user consent, health related websites must ask consent before any data processing, in particular when they embed third party trackers. Admittedly, it is very hard for owners of such websites to both detect the complex tracking practices that exist today and to ensure legal compliance. In this research work, ee proposed Ernie, a browser extension we designed to visualise six state-of-the-art tracking techniques based on cookies. Using Ernie, we analysed 385 health related websites that users would visit when searching for doctors in Germany, Austria, France, Belgium, and Ireland. More specifically, we explored the tracking behavior before any interaction with the consent pop-up and after rejection of cookies on websites of doctors, hospitals, and health related online phone-books. We found that at least one form of tracking occurs on 62% of the websites before interacting with the consent pop-up, and 15% of websites include tracking after rejection. Finally, we performed a detailed technical and legal analysis of three health related websites that demonstrate impactful legal violations. This paper shows that while, from a legal point of view, health related websites are more privacy-sensitive than other kinds of websites, they are exposed to the same technical difficulties to implement a legally compliant website. We believe Ernie, the browser extension we developed, to be an invaluable tool for policy-makers and regulators to improve detection and visualization of the complex tracking techniques used on these websites. The results are published in the Workshop on Privacy in the Electronic Society 25 and the software is described in 33.

8.2.1 On Accounting for Screen Resolution in Adaptive Video Streaming: QoE driven bandwidth sharing framework

Participants: Othmane Belmoukadam, Chadi Barakat.

Screen resolution along with network conditions are main objective factors impacting the user experience, in particular for video streaming applications. User terminals on their side feature more and more advanced characteristics resulting in different network requirements for good visual experience. Previous studies tried to link MOS (Mean Opinion Score) to video bitrate for different screen types (e.g., Common Intermediate Format (CIF), Quarter Common Intermediate Format (QCIF), and High Definition (HD)). We leverage such studies and formulate a QoE driven resource allocation problem to pinpoint the optimal bandwidth allocation that maximizes the QoE over all users of a network service provider located behind the same bottleneck link, while accounting for the characteristics of the screens they use for video playout. For our optimization problem, QoE functions are built using curve fitting on datasets capturing the relationship between MOS, screen characteristics, and bandwidth requirements. We propose a simple heuristic based on Lagrangian relaxation and KKT (Karush Kuhn Tucker) conditions to efficiently solve the optimization problem. Our numerical simulations show that the proposed heuristic is able to increase overall QoE up to 20% compared to an allocation with a TCP look-alike strategy implementing max-min fairness. Results of this work are published in the Journal of Network Management 12.

8.2.2 QoE-driven Cache Placement for Adaptive Video Streaming: Minding the Viewport

Participants: Othmane Belmoukadam, Chadi Barakat.

To handle the increasing demand for video streaming, ISP's and service providers use edge servers to cache video content to reduce the rush on their servers, balance the load between them and over the network, and smooth out the traffic variability. The dynamic adaptive streaming over HTTP protocol (DASH) makes videos available in multiple representations, and end-users can switch video resolution as a function of their network conditions and terminal display capacity (e.g., bandwidth, screen resolution). In this context, we study a viewport-aware caching optimization problem for dynamic adaptive video streaming that appropriately considers the client viewport size and access speed, the join time, and the characteristics of videos. We formulate and study the proposed optimization problem as an Integer Linear Program (ILP) that balances minimal join time and maximal visual experience, subject to the cache storage capacity. Our framework sheds light on optimal caching performance. Our proposed heuristic provides guidelines on the videos, and the representations of each video, to cache based on the video popularity, its encoding information, and the distribution of end-user display capacity and access speed in a way to maximize the overall end-user QoE. This work fits within the PhD thesis of Othmane Belmoukadam 26 and was first published in 19.

8.2.3 Machine Learning for Next-Generation Intelligent Transportation Systems

Participants: Chadi Barakat, Thierry Turletti.

Intelligent Transportation Systems, or ITS for short, includes a variety of services and applications such as road traffic management, traveler information systems, public transit system management, and autonomous vehicles, to name a few. It is expected that ITS will be an integral part of urban planning and future cities as it will contribute to improved road and traffic safety, transportation and transit efficiency, as well as to increased energy efficiency and reduced environmental pollution. On the other hand, ITS poses a variety of challenges due to its scalability and diverse quality-of-service needs, as well as the massive amounts of data it will generate. In the Transactions on emerging telecommunications technologies journal, we published a survey that explores the use of Machine Learning (ML), which has recently gained significant traction, to enable ITS. We provided a comprehensive survey of the current state-of-the-art of how ML technology has been applied to a broad range of ITS applications and services, such as cooperative driving and road hazard warning, and identify future directions for how ITS can use and benefit from ML technology 16.

8.2.4 Dynamic Controller Assignment in Software Defined Internet of Vehicles through Multi-Agent Deep Reinforcement Learning

Participants: Chadi Barakat, Thierry Turletti.

We introduced a novel dynamic controller assignment algorithm targeting connected vehicle services and applications, also known as Internet of Vehicles (IoV). The proposed approach considers a hierarchically distributed control plane, decoupled from the data plane, and uses vehicle location and control traffic load to perform controller assignment dynamically. We modeled the dynamic controller assignment problem as a multi-agent Markov game and solve it with cooperative multi-agent deep reinforcement learning. Simulation results using real-world vehicle mobility traces showed that the proposed approach outperforms existing ones by reducing control delay as well as packet loss. This work has been published in the IEEE Transactions on Network and Service Management journal 17.

8.2.5 Harnessing UAVs for Fair 5G Bandwidth Allocation in Vehicular Communication via Deep Reinforcement Learning

Participants: Chadi Barakat, Thierry Turletti.

Terrestrial wireless infrastructure-based networks do not always guarantee that their resources will be shared uniformly by nodes in vehicular networks mostly due to the uneven and dynamic distribution of vehicles in the network as well as path loss effects. In this wor we leveraged multiple fifth-generation (5G) unmanned aerial vehicles (UAVs) to enhance network resource allocation among vehicles by positioning UAVs on-demand as "flying communication infrastructure". We proposed a deep reinforcement learning (DRL) approach to determine the position of UAVs in order to improve the fairness and efficiency of network resource allocation while considering the UAVs' flying range, communication range, and limited energy resources. We used a parametric fairness function for resource allocation that can be tuned to reach different allocation objectives ranging from maximizing the total throughput of vehicles, maximizing minimum throughput, as well as achieving proportional bandwidth allocation. Simulation results showed that the proposed DRL approach to UAV positioning can help improve network resource allocation according to the targeted fairness objective. These results are published in the IEEE Transactions on Network and Service Management journal 18.

8.2.6 Cross-layer Loss Discrimination Algorithms for MEC in 4G networks

Participants: Mamoutou Diarra, Thierry Turletti, Walid Dabbous.

Traditional loss-based Congestion Control Algorithms (CCAs) suffer from performance issues over wireless networks mostly due to their inability to distinguish wireless random losses from congestion losses. Different loss discrimination algorithms have been proposed to tackle this issue but they are not efficient for 4G networks since they do not consider the impact of various link layer mechanisms such as adaptive modulation and coding and retransmission techniques on congestion in LTE Radio Access Networks (RANs). We proposed MELD (MEC-based Edge Loss Discrimination), a novel server-side loss discrimination mechanism that leverages recent advancements in Multi-access Edge Computing (MEC) services to discriminate packet losses based on real-time RAN statistics. Our approach collects the relevant radio information via MEC's Radio Network Information Service and uses it to correctly distinguish random losses from congestion losses. Our experimental study made with the QUIC transport protocol shows over 80% higher goodput when MELD is used with NewReno and 8% higher goodput when used with Cubic. This work has been presented at the IEEE International Conference on High Performance Switching and Routing (HPSR) conference in June 2021 at Paris 21.

8.2.7 RAN-aware Proxy-based Flow Control for High Throughput and Low Delay eMBB

Participants: Mamoutou Diarra, Thierry Turletti, Walid Dabbous.

5G enhanced Mobile broadband (eMBB) aims to provide users with a peak data rate of 20 Gbps in the Radio Access Network (RAN). However, since most Congestion Control Algorithms (CCAs) rely on startup and probe phases to discover the bottleneck bandwidth, they cannot quickly utilize the available RAN bandwidth and adapt to fast capacity changes without introducing large delay increase, especially when multiple flows are sharing the same Radio Link Control (RLC) buffer. To tackle this issue, we proposed RAPID, a RAN aware proxy-based flow control mechanism that prevents CCAs from overshooting more than the available RAN capacity while allowing near optimal link utilization. Based on analysis of up-todate radio information using Multi-access Edge Computing (MEC) services and packet arrival rates, RAPID is able to differentiate slow interactive flows from fast download flows and allocate the available bandwidth accordingly. Our experiments with concurrent Cubic and BBR flows show that RAPID can reduce delay increase by a factor of 10 to 50 in both Line-of-Sight (LOS) and Non-LOS (NLOS) conditions while preserving high throughput. To handle the ever growing demand of resource intensive experiments distributed, network emulation tools such as Mininet and Maxinet have been proposed. They automatically allocate experimental resources. In this work, we show that resources are poorly allocated, leading to resource overloading and hence to dubious experimental results. This is why we propose and implement a new placement module for distributed emulation. Our algorithms take into account both link and node resources and minimize the number of physical hosts needed to carry out the emulation. Through extensive numerical evaluations, simulations, and actual experiments , we show that our placement methods outperform existing ones and allowing to re-establish trust in experimental results. This work has been presented at the 24th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM) conference in November 2021 at Alicante, Spain 22.

8.2.8 Robust Programmable Networks

Participants: Giuseppe Di Lena, Damien Saucez, Thierry Turletti.

More than ever, data networks have demonstrated their central role in the world economy, but also in the well-being of humanity that needs fast and reliable networks. In parallel, with the emergence of NFV and SDN, efficient network algorithms considered too hard to be put in practice in the past now have a second chance to be considered again. In this context, as new networks will be deployed and current ones get significant upgrades, it is thus time to rethink the network dimensioning problem with protection against failures. In this work, we considered a path-based protection scheme with the global rerouting strategy in which, for each failure situation, there may be a new routing of all the demands. Our optimization task was to minimize the needed amount of bandwidth. We developed two scalable mathematical models that we handle using both Column Generation and Benders Decomposition techniques. Through extensive simulations on real-world IP network topologies and on randomly generated instances, we showed the effectiveness of our methods: they lead to savings of 40 to 48% of the bandwidth to be installed in a network to protect against failures compared to traditional schemes. Our implementation in OpenDaylight demonstrates the feasibility of the approach. Its evaluation with Mininet shows that our solution provides sub-second recovery times, but the way it is implemented may greatly impact the amount of signaling traffic exchanged. In our evaluations, the recovery phase requires only a few tens of milliseconds for the fastest implementation, compared to a few hundreds of milliseconds for the slowest one. This work has been done in collaboration with the COATI team and has been published in the Computer Networks journal 15.

8.3.1 Time Sensitive Networks Evaluation

Participants: Damien Saucez.

Since he's back from Safran (October 2020), Damien Saucez has been working on developing a Time Sensitive Networking (TSN) simulation module for OMNeT++  37. This simulation module is designed for industrial usage and thus closely follows the standards. The idea here is that most potential industrial actors that would use the simulator have no real developper or networking simulation teams. Instead they have large pool of engineers used to read standards and evaluate appliances provided by third parties. Therefore it is essential to provide a solution that is as close as possible to what their day-to-day business is. As a consequence, some choices for the implementation of the simulation would appear inefficient for the ones used to write network simulators but they are not the target of the tool. Our focus on being usable directly by R&D teams in industries explains why exceptionally were are not using ns-3. In addition, as most corporate environments wouldn't allow to install specific development tools, we are working on providing a cloud based support for simulation that we call Simulation-as-a-Service. The backend is an Omnest (the commercial version of OMNeT++) engine while the frontend is purely javascript (REACT) such that simulations can be designed and analysed directly from a web browser. As OMNeT++ relies on a relatively old C++ technology writing a purely reactive javascript simulation environment for OMNeT++ is somehow challenging since nothing as really been thought for such usage.

8.3.2 Distrinet: Distributed Network Emulation

Participants: Giuseppe Di Lena, Damien Saucez, Thierry Turletti.

Networks have become complex systems that combine various concepts, techniques, and technologies. As a consequence, modelling or simulating them now is extremely complicated and researchers massively resort to prototyping techniques. Mininet is the most popular tool when it comes to evaluate SDN propositions. Mininet allows to emulate SDN networks on a single computer but shows its limitations with resource intensive experiments as the emulating host may become overloaded. To tackle this issue, we proposed Distrinet, a distributed implementation of Mininet over multiple hosts, based on LXD/LXC, Ansible, and VXLAN tunnels. Distrinet uses the same API than Mininet, meaning that it is compatible with Mininet programs. It is generic and can deploy experiments on Linux clusters (e.g., Grid'5000), as well as on the Amazon EC2 cloud platform. This tool and an evaluation of its performance has been published in the ACM Computer Communication Review (CCR) journal 14. This work has been done in collaboration with the COATI team.

8.3.3 A Right Placement Makes a Happy Emulator: a Placement Module for Distributed SDN/NFV Emulation

Participants: Giuseppe Di Lena, Damien Saucez, Thierry Turletti.

To handle the ever growing demand of resource intensive experiments distributed, network emulation tools such as Mininet and Maxinet have been proposed. They automatically allocate experimental resources. In this work, we showed that resources are poorly allocated, leading to resource overloading and hence to dubious experimental results. This is why we proposed and implemented a new placement module for distributed emulation. Our algorithms take into account both link and node resources and minimize the number of physical hosts needed to carry out the emulation. Through extensive numerical evaluations, simulations, and actual experiments , we showed that our placement methods outperform existing ones and allowing to re-establish trust in experimental results. This work is reported in 30 and has been presented at the IEEE International Conference on Communications (ICC) conference in June 2021 at Montréal, Canada 20. This work has been done in collaboration with the COATI team.

8.3.4 CloudTrace Demo: Tracing Cloud Network Delay

Participants: Giuseppe Di Lena, Damien Saucez, Thierry Turletti.

Many companies and organizations are moving their applications from on-premises data centers to the cloud. The cloud infrastructures can potentially provide an infinite amount of computation (e.g., Elastic Compute) and storage (e.g., Simple Service Storage). In addition, all cloud providers propose different offers: IaaS, PaaS, and SaaS. In June 2021, we presented a demo at the IEEE International Conference on Network Softwarization (NetSoft) virtual conference that focuses on the IaaS services. In a nutshell, we presented a simple tool to measure the network delay in a virtual infrastructure built entirely in the cloud. These measurements are useful for organizations that are moving current applications to, or creating new applications in, the cloud, but have requirements on the maximum, or average, network delay that these applications can tolerate. We showcased CloudTrace, a simple CLI tool that allows regional and multiregional experiments to measure delay, using Amazon AWS 32. This work has been done in collaboration with the COATI team.

8.3.5 Passive Delay Measurement for Fidelity Monitoring of Distributed Network Emulation

Participants: Houssam Elbouanani, Chadi Barakat, Walid Dabbous, Thierry Turletti.

Emulation has become a popular approach for the validation and evaluation of network research. It provides researchers with a contained, customizable, and scalable testing environment, which can be easily packaged and published for potential readers to reproduce their results. However, as the network components are only virtual, emulation lacks the inherent realism of physical testbeds. In light of this, monitoring specific metrics of the emulated network has been proposed as a solution to mitigate to some degree inaccuracies caused by emulation. While this is not difficult to implement in a single-machine setting (e.g. with Mininet), monitoring is limited by the lack of time synchronization in scenarios where the emulation is distributed over multiple physical machines (e.g., Distrinet). In this work which fits within the PhD thesis of Houssam ElBouanani, we tackle the case of packet delay monitoring, to which we propose a methodology for passively measuring one-way delays with underlying assumptions about time synchronization, and round-trip delays otherwise. For an efficient implementation of our methodology, we propose an eBPF-based packet measurement tool that performs better than current packet sniffers under emulation-specific assumptions. We implement and evaluate our system in an open testbed and show that it can reach results within few microseconds of perfect accuracy and precision. This work was published in 23 and is currently under further development for its usage for network experimentation fidelity monitoring.

Collaboration with Ekinops

Participants: Walid Dabbous, Mamoutou Diarra, Thierry Turletti.  

We have started a collaboration with Ekinops on the topic of Multi-access Edge Computing. The activity started with a CIFRE thesis. The PhD student Mamoutou Diarra started his PhD on this topic on November 2019. Currently, he is working on efficient congestion control mechanisms for 5G scenarios in mutli-access edge environments.

Collaboration with Orange Labs

Participant: Giuseppe Di Lena, Damien Saucez, Thierry Turletti.  

We have a collaboration with Orange Labs on the topic of Network Function Virtualization. The activity includes the CIFRE PhD thesis of Giuseppe Di Lena that started his PhD on resilient NFV/SDN environments on April 2018 co-supervised by Thierry Turletti and Frédéric Giroire from the COATI project-team.

Collaboration with YDATA

Participant: Chadi Barakat, Walid Dabbous Bernard Tamba Sandouno, Thierry Turletti.  

We have started a collaboration with YDATA on the topic of geolocation assessment of mobile network performance. The activity started with a CIFRE thesis. The PhD student Bernard Tamba Sandouno started his PhD on this topic on May 2021. Currently, he is working on developing a tool to predict the geolocation performance of mobile broadband networks using a ray tracing approach coupled with wireless channel propagation models.

QWANT

Participant: Arnaud Legout.  

The PIA ANSWER project is led by the QWANT search engine and the Inria Sophia Antipolis Méditerranée research center. This proposal is the winner of the “Grand Challenges du Numérique” (BPI) and aims to develop the new version of the search engine QWANT with radical innovations in terms of search criteria, indexed content and privacy of users. In the context of this project, we got with Nataliia Bielova from the INDES project-team in 2018, a funding for a 3 years Ph.D. working on Web tracking technologies and privacy protection.

10.1.1 Associate Teams in the framework of an Inria International Lab or in the framework of an Inria International Program

10.2.1 Visits of international scientists

10.3.1 FP7 & H2020 projects

10.3.2 Other European programs/initiatives

ESFRI, the European Strategy Forum on Research Infrastructures, is a strategic instrument to develop the scientific integration of Europe and to strengthen its international outreach. Our project team has-been involved in the last year in the preparation of a large-scale infrastructure projet called SLICES-RI (Scientific LargeScale Infrastructure for Computing/Communication Experimental Studies-Research Infrastructure) that was finally accepted on the ESFRI roadmap for funding. Consortium members of this long term project are eligible to specific calls to design, bootstrap, deploy and operate a european wide flexible platform designed to support large-scale, experimental research focused on networking protocols, radio technologies, services, data collection, parallel and distributed computing and in particular cloud and edge-based computing architectures and services. The DIANA project-team is involved in the main SLICES-RI and two companion projects: SLICES-DS focused on the Design Study of the Research Infrastructure) and SLICES-SC focused on bootstrapping the users community for the RI. Here follows more detail on SLICES-SC.

11.2.1 Teaching

• Master 2 Ubinet: Chadi Barakat and Walid Dabbous, Evolving Internet, 31.5 hours, M2, Université Côte d'Azur, France.
• Master 2 Ubinet: Chadi Barakat and Walid Dabbous, Internet Measurements and New Architectures, 31.5 hours, M2, Université Côte d'Azur, France.
• Master 1 in Computer Science: Chadi Barakat, Computer Networks, 30 hours, M1, Université Côte d'Azur, France.
• Master 2 Estel: Chadi Barakat, Voice over IP, 9 hours, Université Côte d'Azur, France.
• Master Ubinet: Arnaud Legout, From BitTorrent to Privacy, 22.5 hours, M2, Université Côte d'Azur, France.
• Master module AWARE (Awarness-Raising to research) : Arnaud Legout, lecture 2 hours, Eurecom, France.
• Thierry Parmentelat helps coordinating the CS courses for the 1st year students of École des Mines de Paris, covering general topics like Numerical Programming with Python, Advanced Python Programming, and Introduction to Web technologies.

• E-learning
  • Python: Arnaud Legout and Thierry Parmentelat are co-authors of the MOOC: “Python 3 : des fondamentaux aux concepts avancés du langage”. Since its creation in 2014, this MOOC has reached a consolidated number of 111 907 registered students and 10948 attestations. This MOOC is in French, as we felt like there was a gap in the previous offering, with the vast majority of teaching resources available in English only.

11.2.2 Supervision

11.2.3 Juries

• Chadi Barakat served as examiner of Duncan Deveaux's PhD thesis, "On the Networking of Knowledge in Vehicular Networks”, defended in December 2021, at Eurecom.
• Chadi Barakat served as examiner and president of Ishani Sarkar’s PhD thesis, "Data mining and optimisation of a multi-content hybrid P2P/Web distribution network”, defended in November 2021, at I3S and Université Côte d’Azur.
• Chadi Barakat served as examiner of Flavia Salutari’s PhD thesis, "Longitudinal, large-scale and unbiased Internet measurements”, defended in September 2021, at Telecom Paris.
• Chadi Barakat served as reviewer of Loick Bonniot’s PhD thesis, "Computer Network Modeling and Root Cause Analysis with Statistical Learning”, defended in June 2021, at Université de Rennes 1.
• Chadi Barakat served as jury member for the mid-term review of Raza Ul Mustafa’s PhD thesis, “Machine Learning Assisted DASH QoE Inference Through Network Level QoS Feature”, University of Campinas, Brazil, held in October 2021.
• Chadi Barakat served as jury member for the mid-term review of Zhejiayu Ma’s PhD thesis, “Machine learning in the context of WebRTC-based multimedia diffusion”, EasyBroadcast and Université Côte d'Azur, held in May 2021.
• Walid Dabbous served as mentor and jury member for the HDR of Nataliia Bielova on "Protecting Privacy of Web Users" defended on June 7, 2021 at Université Côte d'Azur.
• Walid Dabbous served as reviewer and jury member for the HDR of Hicham Lakhlef on "Towards scalable and secure control in wireless communicating things" defended on December 3, 2021 at University of Technology, Compiègne.
• Walid Dabbous served jury president for the PhD of Luca Santamaria on "Integrated Reconfigurable Antenna Systems for Dynamic Wireless IoT Networks" defended on December 13, 2021 at Université Côte d'Azur.
• Thierry Turletti served as reviewer of Anouar Rkhami's PhD thesis “From services placement to services monitoring in 5G and post-5G networks”, defended on December 14, 2021 at Université de Rennes 1.
• Thierry Turletti served as examiner of Adrien Thibaud's PhD thesis “Répartition de flux dans les réseaux de contenu, application à un contexte satellite”, defended on September 2, 2021 at INP Toulouse.
• Thierry Turletti served as reviewer of Adrien Wion's PhD thesis “Control Plane in Dynamic Software Networks, defended on March 5, 2021 at Telecom Paris.
• Thierry Turletti served as examiner and president of El Fadel Bonfoh's PhD thesis “VTL : Une Architecture Stable pour la Conception, l’Implémentation, et le Déploiement de Protocoles de Communication d’Internet”, defended on January 26, 2021 at INSA Toulouse.
• Thierry Turletti served as reviewer of Salma Matoussi's PhD thesis “User-Centric Slicing with Functional Splits in 5G Cloud-RAN”, defended on January 22, 2021 at Sorbonne Université.

11.3.1 Internal or external Inria responsibilities

Damien Saucez is chargé de mission médiation scientifique interne. The role is to promote and favour scientific exchanges between Sophia’s center researchers but also to popularise sciences within the center, not only for the researchers but for all personnel of the center.

The two main activities that are put in place are the so-called In’tro and Café In.

The concept of In’Tro has been proposed by Fabien Gandon and we implemented it successfully in March 2021. In’Tro aim to promote recently hired researcher in order to foster new collaborations. Every month, a researcher is allocated a slot of 30 minutes during lunch time to presents her/his work during 15 minutes and to answer questions during 15 minutes. Due to the pandemics the 8 events of 2021 were purely virtual meetings. Presentations are made publicly available on VoD. On average we counted about 30 live attendees. We also observe that the videos are watched on demand after the presentation, not only by Inria people but also by anonymous viewers that received YouTube suggestions.

The Café-In events are different in their objective and organised since 2012. Once a month a one hour slot is dedicated to popularise sciences to Inria personel, regardless of whether they are scientific or not. After lunch, a researcher, or a panel of researchers, is invited to talk about a subject of his/her choice around a coffee. The main objective is not to foster new collaborations but to allow everyone at Inria to understand important research subjects that are work on by Inria researchers and to open their curiosity. Because of the constrains imposed by the pandemic it was not possible in 2021 to really talk around a coffee and even though the 6 talks that has been organised were of high quality, we noticed very low attendance levels compared to “normal years”. Nevertheless, similarly to the In’Tros, talk have been recorded and are publicly available and views are increasing from month to month.

In parallel, we promoted the use of the center’s zimbra calendar to advertise internal team seminars. As of now, we lack of indicators to determine if this calendar has boosted inter-team or cross disciplines collaborations.

For more information, check the MASTIC website.

11.3.2 Interventions

Damien Saucez made 4 Chiche! sessions this year. See the Chiche Web site.

Walid Dabbous presented R2lab and an introduction to electromagntic waves to young interns from different schools on december 16, 2021.

Walid Dabbous gave a presentaton to "Lycée" students in the context of "La fête de la Science" on October 4, 2021. The video was published on YouTube.

Bernard Tamba Sandounou presented his work on predict the performance of mobile networks using geometric methods and wireless channel propagation models in the "Nuit Européenne des chercheur.es" at Université Côte d'Azur on September 24, 2021.

International journals

• 11 articleO.Othmane Belmoukadam and C.Chadi Barakat. Unveiling the end-user viewport resolution from encrypted video traces.IEEE Transactions on Network and Service Management183September 2021, 3324-3335
  HALDOIback to text
• 12 articleO.Othmane Belmoukadam, M. J.Muhammad Jawad Khokhar and C.Chadi Barakat. On Accounting for Screen Resolution in Adaptive Video Streaming: QoE driven bandwidth sharing framework.International Journal of Network Management311January 2021, e2128
  HALDOIback to text
• 13 articleY.Yanis Boussad, M. N.Mohamed Naoufal Mahfoudi, A.Arnaud Legout, L.Leonardo Lizzi, F.Fabien Ferrero and W.Walid Dabbous. Evaluating Smartphone Accuracy for RSSI Measurements.IEEE Transactions on Instrumentation and Measurement70January 2021, 1 - 12
  HALDOIback to text
• 14 articleG.Giuseppe Di Lena, A.Andrea Tomassilli, D.Damien Saucez, F.Frédéric Giroire, T.Thierry Turletti and C.Chidung Lac. Distrinet: a Mininet Implementation for the Cloud.Computer Communication Review511January 2021, 2-9
  HALDOIback to text
• 15 articleA.Andrea Tomassilli, G.Giuseppe Di Lena, F.Frédéric Giroire, I.Issam Tahiri, D.Damien Saucez, S.Stéphane Pérennes, T.Thierry Turletti, R.Ruslan Sadykov, F.François Vanderbeck and C.Chidung Lac. Design of Robust Programmable Networks with Bandwidth-optimal Failure Recovery Scheme.Computer Networks192108043June 2021
  HALDOIback to text
• 16 articleT.Tingting Yuan, W. B.Wilson Borba Da Rocha Neto, C. E.Christian Esteve Rothenberg, K.Katia Obraczka, C.Chadi Barakat and T.Thierry Turletti. Machine Learning for Next-Generation Intelligent Transportation Systems: A Survey.Transactions on emerging telecommunications technologies2021
  HALback to text
• 17 articleT.Tingting Yuan, W. D.Wilson Da Rocha Neto, C. E.Christian Esteve Rothenberg, K.Katia Obraczka, C.Chadi Barakat and T.Thierry Turletti. Dynamic Controller Assignment in Software Defined Internet of Vehicles through Multi-Agent Deep Reinforcement Learning.IEEE Transactions on Network and Service Management181March 2021, 12
  HALDOIback to text
• 18 articleT.Tingting Yuan, C. E.Christian Esteve Rothenberg, K.Katia Obraczka, C.Chadi Barakat and T.Thierry Turletti. Harnessing UAVs for Fair 5G Bandwidth Allocation in Vehicular Communication via Deep Reinforcement Learning.IEEE Transactions on Network and Service Management2021
  HALback to text

International peer-reviewed conferences

• 19 inproceedingsO.Othmane Belmoukadam and C.Chadi Barakat. QoE-driven Cache Placement for Adaptive Video Streaming: Minding the Viewport.MeditCom 2021 - IEEE International Mediterranean Conference on Communications and NetworkingAthènes, GreeceSeptember 2021
  HALDOIback to text
• 20 inproceedingsG.Giuseppe Di Lena, A.Andrea Tomassilli, F.Frédéric Giroire, D.Damien Saucez, T.Thierry Turletti and C.Chidung Lac. A Right Placement Makes a Happy Emulator: a Placement Module for Distributed SDN/NFV Emulation.ICC 2021 - IEEE International Conference on CommunicationsMontréal, CanadaIEEEJune 2021
  HALDOIback to text
• 21 inproceedingsM.Mamoutou Diarra, W.Walid Dabbous, A.Amine Ismail and T.Thierry Turletti. Cross-layer Loss Discrimination Algorithms for MEC in 4G networks.IEEE International Conference on High Performance Switching and Routing (HPSR)Paris, FranceJune 2021
  HALback to text
• 22 inproceedingsM.Mamoutou Diarra, W.Walid Dabbous, A.Amine Ismail and T.Thierry Turletti. RAN-aware Proxy-based Flow Control for High Throughput and Low Delay eMBB.24th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)Alicante, SpainNovember 2021
  HALback to text
• 23 inproceedingsH.Houssam Elbouanani, C.Chadi Barakat, W.Walid Dabbous and T.Thierry Turletti. Passive Delay Measurement for Fidelity Monitoring of Distributed Network Emulation.MedComNet 2021 - 19th Mediterranean Communication and Computer Networking ConferenceVirtual, FranceJune 2021
  HALDOIback to text
• 24 inproceedingsG.Giulio Grassi, R.Renata Teixeira, C.Chadi Barakat and M.Mark Crovella. Leveraging Website Popularity Differences to Identify Performance Anomalies.INFOCOM 2021 - IEEE International Conference on Computer CommunicationsVancouver / Virtual, CanadaMay 2021
  HALDOIback to text

Conferences without proceedings

• 25 inproceedingsV.Vera Wesselkamp, I.Imane Fouad, C.Cristiana Santos, Y.Yanis Boussad, N.Nataliia Bielova and A.Arnaud Legout. In-Depth Technical and Legal Analysis of Tracking on Health Related Websites with ERNIE Extension.20th Workshop on Privacy in the Electronic SocietySeoul, South KoreaNovember 2021
  HALback to text

Doctoral dissertations and habilitation theses

• 26 thesisO.Othmane Belmoukadam. QoE-aware content management in the Internet : caching and transport.Université Côte d'AzurSeptember 2021
  HALback to textback to textback to text
• 27 thesisY.Yanis Boussad. Large-scale characterization of exposure to downlink radiofrequencies.DIANA; Laboratoire d’Electronique, Antennes et Télécommunications; Université Côté d’AzurSeptember 2021
  HALback to text
• 28 thesisG.Giuseppe Di Lena. Distributed and trustable SDN-NFV-enabled network emulation on testbeds and cloud infrastructures.Université Côte d'AzurMarch 2021
  HALback to text

Reports & preprints

• 29 miscY.Yanis Boussad, X. L.Xi Leslie Chen, A.Arnaud Legout, A.Augustin Chaintreau and W.Walid Dabbous. Longitudinal Study of Exposure to Radio Frequencies at Population Scale.Inria & Université Nice Sophia Antipolis, CNRS, I3S, Sophia Antipolis, France; Columbia UniversityOctober 2021
  HALback to text
• 30 reportG.Giuseppe Di Lena, A.Andrea Tomassilli, F.Frédéric Giroire, D.Damien Saucez, T.Thierry Turletti and C.Chidung Lac. Placement Module for Distributed SDN/NFV Network Emulation.RR-9391Inria Sophia Antipolis - Méditerranée; I3S, Université Côte d'Azur; Orange Labs R&D [Lannion] (France Télécom)February 2021, 32
  HALback to text
• 31 miscI.Imane Fouad, C.Cristiana Santos, A.Arnaud Legout and N.Nataliia Bielova. Did I delete my cookies? Cookies respawning with browser fingerprinting.May 2021
  HALback to text

Other scientific publications

• 32 inproceedingsG.Giuseppe Di Lena, F.Frédéric Giroire, T.Thierry Turletti and C.Chidung Lac. CloudTrace Demo: Tracing Cloud Network Delay.IEEE International Conference on Network Softwarization (NetSoft)Fully Virtual, FranceIEEEJune 2021
  HALDOIback to text

Softwares

• 33 softwareV.Vera Wesselkamp, I.Imane Fouad, A.Arnaud Legout and N.Nataliia Bielova. Ernie Extension.November 2021GNU General Public License v3.0 only
  HALSoftwage HeritageVCSback to text