2023Activity reportProject-TeamSTACK

7.1.1 ENOS

• Name:
  Experimental eNvironment for OpenStack
• Keywords:
  OpenStack, Experimentation, Reproducibility
• Functional Description:

  Enos workflow :

  A typical experiment using Enos is the sequence of several phases: - enos up : Enos will read the configuration file, get machines from the resource provider and will prepare the next phase - enos os : Enos will deploy OpenStack on the machines. This phase rely highly on Kolla deployment. - enos init-os : Enos will bootstrap the OpenStack installation (default quotas, security rules, ...) - enos bench : Enos will run a list of benchmarks. Enos support Rally and Shaker benchmarks. - enos backup : Enos will backup metrics gathered, logs and configuration files from the experiment.

• URL:
  https://­github.­com/­BeyondTheClouds/­enos
• Publication:
  hal-01664515
• Contact:
  Adrien Lebre
• Participants:
  Mathieu Simonin, Marie Delavergne, Adrien Lebre, Baptiste Jonglez
• Partner:
  Orange Labs

7.1.2 EnOSlib

• Name:
  EnOSlib is a library to help you with your experiments
• Keywords:
  Distributed Applications, Distributed systems, Evaluation, Grid Computing, Cloud computing, Experimentation, Reproducibility, Linux, Virtualization
• Functional Description:

  EnOSlib is a library to help you with your distributed application experiments. The main parts of your experiment logic is made reusable by the following EnOSlib building blocks:

  - Reusable infrastructure configuration: The provider abstraction allows you to run your experiment on different environments (locally with Vagrant, Grid’5000, Chameleon and more) - Reusable software provisioning: In order to configure your nodes, EnOSlib exposes different APIs with different level of expressivity - Reusable experiment facilities: Tasks help you to organize your experimentation workflow.

  EnOSlib is designed for experimentation purpose: benchmark in a controlled environment, academic validation …

• URL:
  https://­discovery.­gitlabpages.­inria.­fr/­enoslib/
• Publications:
  hal-01664515, hal-01689726
• Contact:
  Mathieu Simonin
• Participants:
  Mathieu Simonin, Baptiste Jonglez, Marie Delavergne, Alexis Bitaillou

7.1.3 Concerto

• Name:
  Concerto
• Keywords:
  Reconfiguration, Distributed Software, Component models, Dynamic software architecture
• Functional Description:
  Concerto is an implementation of the formal model Concerto written in Python. Concerto allows to : 1. describe the life-cycle and the dependencies of software components, 2. describe a components assembly that forms the overall life-cycle of a distributed software, 3. automatically reconfigure a Concerto assembly of components by using a set of reconfiguration instructions as well as a formal operational semantics.
• URL:
  https://­gitlab.­inria.­fr/­VeRDi-project/­concerto
• Publications:
  hal-03103714, hal-02535077, hal-01897803
• Contact:
  Hélène Coullon
• Participants:
  Christian Perez, Hélène Coullon, Maverick Chardet, Simon Robillard
• Partners:
  IMT Atlantique, LS2N, LIP

7.1.4 6TiSCH Simulator

• Name:
  High-level simulator of a 6TiSCH network
• Keywords:
  Network simulator, 6TiSCH
• Functional Description:
  The simulator is written in Python. While it doesn't provide a cycle-accurate emulation, it does implement the functional behavior of a node running the full 6TiSCH protocol stack. This includes RPL, 6LoWPAN, CoAP and 6P. The implementation work tracks the progress of the standardization process at the IETF.
• Publication:
  hal-03919553
• Contact:
  Malisa Vucinic
• Participant:
  Remous Koutsiamanis

7.2.1 OpenStack

Participants: Geo Johns Antony, Marie Delavergne, Baptiste Jonglez, Matthieu Rakotojaona Rainimangavelo, Adrien Lebre.

OpenStack is the de facto open-source management system to operate and use Cloud Computing infrastructure. Started in 2012, the OpenStack foundation gathers 500 organizations including groups such as Intel, AT&T, RedHat, etc. The software platform relies on tens of services with a 6-month development cycle. It is composed of more than 2 millions of lines of code, mainly in Python, just for the core services. While these aspects make the whole ecosystem quite swift, they are also good signs of maturity for this community.

We created and animated between 2016 and 2018 the Fog/Edge/Massively Distributed (FEMDC) Special Interest Group and have been contributing to the Performance working group since 2015. The former investigates how OpenStack can address Fog/Edge Computing use cases whereas the latter addresses scalability, reactivity and high-availability challenges. In addition to releasing white papers and guidelines 54, the major result from the academic view point is the aforementioned EnOS solution, a holistic framework to conduct performance evaluations of OpenStack (control and data plane). In May 2018, the FEMDC SiG turned into a larger group under the control of the OpenStack foundation. This group gathers large companies such as Verizon, ATT, etc. Although our involvment has been less important since 2020, our participation is still signficant. For instance, we co-signed the second white paper delivered by the edge working group in 2020  55 and are still taking part to the working group, investigating new use-cases as well as resulting challenges.

7.2.2 Grid'5000

Participants: Remous-Aris Koutsiamanis, Baptiste Jonglez, Adrien Lebre, Jean Marc Menaud.

Grid'5000 is a large-scale and versatile testbed for experiment-driven research in all areas of computer science, with a focus on parallel and distributed computing including Cloud, HPC and Big Data. It provides access to a large amount of resources: 12000 cores, 800 compute-nodes grouped in homogeneous clusters, and featuring various technologies (GPU, SSD, NVMe, 10G and 25G Ethernet, Infiniband, Omni-Path) and advanced monitoring and measurement features for traces collection of networking and power consumption, providing a deep understanding of experiments. It is highly reconfigurable and controllable. STACK members are strongly involved into the management and the supervision of the testbed, notably through the steering committee or the SeDuCe testbed described hereafter.

7.2.3 SeDuCe

Participants: Remous-Aris Koutsiamanis, Baptiste Jonglez, Jean Marc Menaud.

The SeDuCe Project aims to deliver a research testbed dedicated to holistic research studies on energetical aspects of datacenters. Part of the Grid'5000 Nantes site, this infrastructure is composed of probes that measure the power consumption of each server, each switch and each cooling system, and also measure the temperature at the front and the back of each servers. These sensors enable reasearch to cover the full spectrum of the energetical aspect of datacenters, such as cooling and power consumption depending of experimental conditions.

The testbed is connected to renewable energy sources (solar panels). This “green” datacenter enables researchers to perform real experiment-driven studies on fields such as temperature based scheduling or “green” aware software (i.e., software that take into account renewable energies and weather conditions).

7.2.4 PiSeDuCe

Participants: Remous-Aris Koutsiamanis, Baptiste Jonglez, Jean Marc Menaud.

In 2023, we consolidated the development of PiSeDuCe, a deployment and reservation system for Edge Computing infrastructures composed of multiple Raspberry Pi Cluster started in 2020. Typically, a cluster of 8 Raspberry Pi costs less than 900 euros and only needs an electrical outlet and a wifi connection for its installation and configuration. Funded by the CNRS through the Kabuto project, and in connection with the SLICES-FR initiative, we have extended PiSeduce to propose a device to cloud deployment system (from devices on Fit IoTLab to servers in Grid’5000). PiSeDuCe and SeDuce led us to submit the Samurai CPER proposal.

7.2.5 SAMURAI

Participants: Remous-Aris Koutsiamanis, Baptiste Jonglez, Jean Marc Menaud.

In 2022 the SAMURAI (Sustainable And autonoMoUs gReen computing for AI) project was accepted, as a part of the energy and digital transition theme. The project aims at reinforcing an innovative hardware infrastructure for the scientific study of the intersecting problems of computing infrastructure that supports artificial intelligence and its energy autonomy. SAMURAI will extend SeDuCe into energy autonomy by adding a smart and clean energy storage system. Additionally, it will extend the capabilities of the platform by adding AI computing nodes (GPUs) for the scientific study of AI tools. Finally, it will also add new sensor nodes within the Nantes connected object platform (Nantes nodes of the national FIT IoT-Lab platform) to support future work on embedded AI. In 2023, We built the IoT platform and network integration with the SeDuCe and G5K platform.

7.2.6 SLICES-FR/SLICES

Participants: Remous-Aris Koutsiamanis, Baptiste Jonglez, Adrien Lebre, Jean Marc Menaud.

STACK Members are involved in the definition and bootstrapping of the SLICES-FR infrastructure. This infrastructure can be seen as a merge of the Grid'5000 and FIT testbeds with the goal of providing a common platform for experimental Computer Science (Next Generation Internet, Internet of things, clouds, HPC, big data, etc.). In 2022, STACK contributions are mainly related to SLICES, the European initiative relative. In particular, members have taken part to the SLICES-DS project (Design Study) as well as the SLICES-PP project (Preparatory Phase) of the SLICES-RI action .

Network resource management:

 The team has continued activities covering the Cloud–IoT continuum. First, an architecture that cover the whole continuum has been proposed in 14. It deploys hierachical federated learning (HFL) to cope with limitations of traditional FL, which suffers from several issues such as (i) robustness, due to a single point of failure, (ii) latency, as it requires a significant amount of communication resources, and (iii) convergence, due to system and statistical heterogeneity. HFL adds the edge servers as an intermediate layer for sub-model aggregation, several iterations will be performed before the global aggregation at the cloud server takes place, thus making the overall process more efficient, especially with non-independent and identically distributed (non-IID) data. Moreover, using traditional Artificial Neural Networks (ANNs) with HFL consumes a significant amount of energy, further hindering the application of decentralized FL on energy-constrained mobile devices. Therefore, this paper presents HFedSNN: an energy-efficient and fast-convergence model by incorporating Spike Neural Networks (SNNs) within HFL. SNN is a generation of neural networks, which promises tremendous energy and computation efficiency improvements. Taking advantage of HFL and SNN, numerical results demonstrate that HFedSNN outperforms FL with SNN (FedSNN) in terms of accuracy and communication overhead by 4.48% and 26×, respectively. Furthermore, HFedSNN significantly reduces energy consumption by 4.3× compared to FL with ANN (FedANN).

Moreover, as the complexity and scale of modern networks continue to grow, the need for efficient, secure management, and optimization becomes increasingly vital. Digital twin (DT) technology has emerged as a promising approach to address these challenges by providing a virtual representation of the physical network, enabling analysis, diagnosis, emulation, and control. The emergence of Software-defined network (SDN) has facilitated a holistic view of the network topology, enabling the use of Graph neural network (GNN) as a data-driven technique to solve diverse problems in future networks. The survey 10 explores the intersection of GNNs and Network digital twins (NDTs), providing an overview of their applications, enabling technologies, challenges, and opportunities. We discuss how GNNs and NDTs can be leveraged to improve network performance, optimize routing, enable network slicing, and enhance security in future networks. Additionally, we highlight certain advantages of incorporating GNNs into NDTs and present two case studies. Finally, we address the key challenges and promising directions in the field, aiming to inspire further advancements and foster innovation in GNN-based NDTs for future networks.

With an orientation specific to 5G networks and cloud computing, in 18 we introduce the Mobile Edge Slice Broker (MESB), a novel solution for orchestrating the deployment and operation of mobile edge slices in multi-cloud environments. We focus on reconciling the challenges faced by mobile edge slice tenants in selecting Cloud Infrastructure Providers (CIPs), ensuring seamless integration of network functions, services, and applications while maintaining quality of service (QoS). Our MESB architectural design enables dynamic monitoring, reconfiguration, and optimization of mobile edge slices to meet evolving requirements. This work represents a first step in enhancing the efficiency and effectiveness of resource management in the convergence of telecom and cloud services in 5G networks.

In line with the previous works in network resource management, in 11 we continue to focus on efficient and secure network management by applying federated learning specifically to 5G cellular traffic prediction. In this work we emphasize the viability of various neural network models, including RNNs and CNNs, in a federated setting for time-series forecasting, while also exploring the effectiveness of different federated aggregation functions in handling non-identically distributed data. Additionally, we demonstrate that preprocessing techniques at local base stations significantly improve prediction accuracy, and that federated learning offers substantial benefits in reducing carbon emissions, computational demands, and communication costs, making it a viable and efficient approach for large-scale and intelligent resource management in network systems.

CloudFactory:

19 introduces CloudFactory, an IaaS workload generator, as a solution to address the representativeness problem. This tool includes a library for sharing IaaS statistics and a generator for producing realistic VM workloads based on these statistics. CloudFactory is offered as open-source software for use by Cloud providers and researchers to facilitate the evaluation of new contributions. To demonstrate the relevance of CloudFactory, we discuss an analysis of the scheduling evolution for different IaaS workload intensities of two different cloud providers (Microsoft Azure and Chameleon). OVHcloud statistics, computed from CloudFactory, are also reported, and a comparison is made with other Cloud providers.

Urgent Computing:

The Continuum Computing encompasses the integration of diverse infrastructures, including cloud, edge, and fog, to facilitate seamless migration of applications based on their specific needs, ensuring optimal satisfaction of their requirements. In particular, Urgent applications aim at processing distributed data sources while considering the uncertainty of infrastructure and timeliness constraints of data-driven workflows. The primary obstacles in this particular context mostly pertain to the incapacity to promptly respond to changes in the environment or the quality of service (QoS) constraints of the application, as well as the incapability to maintain an application in a stateless manner, hence impeding its relocation without the risk of data loss. This line of work is highly motivated by natural disaster case studies. In  17, we leverage three different platforms to combine smoke detection at the edge using camera imagery, wildfire simulations in the cloud, and finally heavy HPC models for generating pollution concentration maps. The resulting workflow is a prime example of a Cloud-to-IoT continuum use case that monitors and manages the air quality impacts of remote wildfires. In this context, we frame challenges and discuss how the R-Pulsar programming system can support urgent data-processing pipelines that tradeoff the content of data, cost of computation, and urgency of the results.

In  24, we tackle the aforementioned issues through the introduction of a framework based on a Function-as-a-Service (FaaS) and event-driven architecture. This framework enables the decomposition, localization, and relocation of applications inside a Continuum infrastructure, facilitated by a rule engine that is both system and data-aware. Results highlight the use the execution history as a basis for determining the optimal location for executing a function, hence guaranteeing the desired Quality of Service (QoS). The evaluation was carried out by simulating a smoke detection use case as a representative scenario for Urgent Computing. We extended this approach in the context of the TEMA Horizon Europe project that aims at addressing Natural Disaster Management 25. We introduced the Urgent Function Enabler (UFE) platform, a fully distributed architecture able to define, spread, and manage FaaS functions, using local IoT data and a computing infrastructure composed of mobile and stable nodes.

This approach presents significant potential in numerous fields. We are currently exploring a climate risk management framework based on real data from the Danish Meteorological and Hydrological Institutes (DMI, and DHI), coupled with road condition (pavement bearing capacity) data from authorities 23. The aim of this project is to enhance a risk assessment model for evaluating pavement structure functionality during extreme weather events.

Fog Modeling:

In 6, we propose a detailed overview of the current state-of-the-art in terms of Fog modeling languages. We relied on our long-term experience in Cloud Computing and Cloud Modeling to contribute a feature model describing what we believe to be the most important characteristics of Fog modeling languages. We also performed a systematic scientific literature search and selection process to obtain a list of already existing Fog modeling languages. Then, we evaluated and compared these Fog modeling languages according to the characteristics expressed in our feature model. As a result, we discuss in this paper the main capabilities of these Fog modeling languages and propose a corresponding set of open research challenges in this area.

The size, complexity, and heterogeneity of Fog systems throughout their life cycle poses challenges and potential costs. To address this, 15 proposes a generic model-based approach called VeriFog, utilizing a customizable Fog Modeling Language (FML) for verifying Fog systems during the design phase. The approach was tested with three use cases from different application domains, considering various non-functional properties for verification (energy, performance, security). Developed in collaboration with the industrial partner Smile, this approach represents a crucial step towards a comprehensive model-based support for the entire life cycle of Fog systems.

Configuration languages:

In the context of the OTPaaS project, we have started to study the anatomy of configuration languages with the objective of unveiling the building blocks of such languages. In particular, we have focused on a very expressive, and declarative, new configuration language, called CUE (CUE stands for Configure Unify Execute). CUE is open source, inspired by previous work at Google. It represents configurations in a way inspired by typed feature structures, a concept inherited from computational linguistics. This is not the first time that a language is built on top of this concept: LIFE, built in the 80s, revolves around psi-terms, a variant of types feature structures. Whereas CUE is a domain-specific language, LIFE is a generic language, which combines logic programming, functional programming and object-oriented programming. As such, it potentially provides a general framework to relate configuration as data and computations. We have presented our initial findings on the relationship between CUE and LIFE at CONFLANG '23, a SPLASH workshop 29.

Software deployment/reconfiguration:

For a few years, the team has been working on deployment and dynamic reconfiguration of distributed software systems through the tool Concerto 42. By offering a programmable lifecycle of resources (services, devices etc.), the team has shown multiple times that the level of parallelism and asynchronism when executing reconfigurations can be increased, thus reducing the execution time of reconfigurations. The accumulated knowledge on component-based distributed software reconfiguration has made possible the publication in 2023 of a survey in ACM Computing Surveys 9, a great success. In particular, this survey analyzes the state of the art on reconfiguration through the spectrum of verification. Indeed, given the complexity of distributed software and the adverse effects of incorrect reconfigurations, a suitable methodology is needed to ensure the correctness of reconfigurations in component-based systems. This survey gives the reader a global perspective over existing formal techniques that pursue this goal. It distinguishes different ways in which formal methods can improve the reliability of reconfigurations, and lists techniques that contribute to solving each of these particular scientific challenges.

In addition to this survey, last year the team has worked on the decentralized version of Concerto, namely Concerto-D. Such decentralized reconfiguration tool is very useful when building global knowledge on the state of the system is difficult, impossible, or very costly because of faults, disconnection or scale. If a publication on Concerto-D itself is not yet published, the usage of Concerto-D has been explored and published on three use cases describe below.

First, Cyber-Physical Systems (CPS) deployed in scarce resource environments like the Arctic Tundra (AT) face extreme conditions. Nodes deployed in such environments have to carefully manage a limited energy budget, forcing them to alternate long sleeping and brief uptime periods. During uptimes, nodes can collaborate for data exchanges or computations by providing services to other nodes. Deploying or updating such services on nodes requires coordination to prevent failures (e.g., sending new/updated API, waiting for service activation/deactivation, etc.). In 20, we study analytically and experimentally, to what extent using relay nodes for communications reduces the deployment and update durations (reconfiguration), and which factors influence this reduction. Intuitively, as dealing with sleeping nodes with low chances of uptime overlaps (no uptime synchronization), a coordinated deployment or update takes very long to finish if nodes have to communicate directly. In 21 we evaluate and study nodes' energy consumption during reconfiguration tasks coordination according to different CPS configurations (i.e., number of nodes, uptime duration, radio technology, or relay node availability). Results show high energy consumption in scenarios where nodes wake up specifically to deploy/update. It is shown that it is beneficial to do adaptation tasks while overlapping with existing uptimes (i.e., reserved for observation activities). This paper also evaluates and studies how nodes' uptime duration and relay node availability influence energy consumption. Increasing uptime duration can reduce energy consumption, up to 12

Second, Concerto-D has been studied and used in the context of the SeMaFoR ANR project. The context of this project is Fog Computing, a paradigm aiming to decentralize the Cloud by geographically distributing away computation, storage and network resources as well as related services. This notably reduces bottlenecks and data movement. However, managing Fog resources is a major challenge because the targeted systems are large, geographically distributed, unreliable and very dynamic. Cloud systems are generally managed via centralized autonomic controllers automatically optimizing both application QoS and resource usage. To leverage the self-management of Fog resources, we propose to orchestrate a fleet of autonomic controllers in a decentralized manner, each with a local view of its own resources. In 13, we present our SeMaFoR (Self-Management of Fog Resources) vision that aims at collaboratively operating Fog resources. SeMaFoR is a generic approach made of three cornerstones: an Architecture Description Language for the Fog, a collaborative and consensual decision-making process, and an automatic coordination mechanism for reconfiguration (based on Concerto-D).

Finally, the usage of Concerto-D has been studied on the particular case of Urgent Computing. This field considers sudden situations of danger such as climate disasters, fires and air pollution, which happen without control in a possibly short window frame, and puts people's lives in danger. In such situation, some applications to help solve the situation have to be dynamically deployed, or existing applications have to be updated in a short period of time and according to new unanticipated constraints. The study in 16 provides a justification for the necessity of dynamic adaptation in applications that are time-sensitive. Furthermore, we present our viewpoint on time-sensitive applications and undertake a thorough analysis of the underlying principles and challenges that need to be resolved in order to accomplish this goal.

Decentralized federated learning:

Federated Learning (FL) collaboratively trains machine learning models on the data of local devices without having to move the data itself: a central server aggregates models, with privacy and performance benefits but also scalability and resilience challenges. We have presented FDFL citedelacour:hal-03946638, a new fully decentralized FL model and architecture that improves standard FL scalability and resilience with no loss of convergence speed. FDFL provides an aggregator-based model that enables scalability benefits and features an election process to tolerate node failures. Simulation results show that FDFL scales well with network size in terms of computing, memory, and communication compared to related FL approaches

Network security and privacy:

The rapid development of network communication along with the drastic increase in the number of smart devices has triggered a surge in network traffic, which can contain private data and in turn affect user privacy. Recently, Federated Learning (FL) has been proposed in Intrusion Detection Systems (IDS) to ensure attack detection, privacy preservation, and cost reduction, which are crucial issues in traditional centralized machine-learning-based IDS. However, FL-based approaches still exhibit vulnerabilities that can be exploited by adversaries to compromise user data. At the same time, meta-models (including the blending models) have been recognized as one of the solutions to improve generalization for attack detection and classification since they enhance generalization and predictive performances by combining multiple base models. Therefore, we have proposed in 7 a Federated Blending model-driven IDS framework for the Internet of Things (IoT) and Industrial IoT (IIoT), called F-BIDS, in order to further protect the privacy of existing ML-based IDS. It consists of a Decision Tree (DT) and Random Forest (RF) as base classifiers to first produce the meta-data. Then, the meta-classifier, which is a Neural Networks (NN) model, uses the meta-data during the federated training step, and finally, it makes the final classification on the test set. Specifically, in contrast to the classical FL approaches, the federated meta-classifier is trained on the meta-data (composite data) instead of user-sensitive data to further enhance privacy. To evaluate the performance of F-BIDS, we used the most recent and open cyber-security datasets, called Edge-IIoTset (published in 2022) and InSDN (in 2020). We chose these datasets because they are recent datasets and contain a large amount of network traffic including both malicious and benign traffic.

Secure biomedical analyzes:

In Wilmer Garzon's PhD thesis 28, he has shown that researchers require new tools and techniques to address the restrictions and needs of global scientific collaborations over geo- distributed biomedical data. He has identified three kinds of constraints related to global collaborations, namely, technical, legal, and socioeconomic constraints.

He has proposed Fully Distributed Collaborations (FDC), which are research endeavors that provide means to analyze massive biomedical information collaboratively while respecting legal and socioeconomic restrictions.

A new random-forest based AI-algorithm MuSiForest improves over other existing AI approaches by ameliorating computation time and reducing the amount of shared data while having a training precision close to that of cen- tralized random forest techniques.

Finally, he has proposed FeDeRa, a language to specify, deploy, and execute FDC-compliant multi-site scientific workflows.

Kelio (formely Bodet Software)

Participants: Thomas Ledoux.

The ArchOps 2 Chair (for Architecture, Deployment and Administration of Agile IT Infrastructures) is an industrial chair of IMT Atlantique, in partnership with Kelio, an SME specialized in solutions for time and attendance management. It is dedicated to all IMT Atlantique students in the field of IT. It is also a channel for the transfer of high-level skills: researchers, experts and industrials.

In 2023, several activities were conducted, such as a hackathon with 100 participants, an event promoting the integration of international students at IMT Atlantique and preliminary discussions on the topic of a joint PhD thesis with the Stack team.

Alterway/Smile

Participants: Thomas Ledoux, Hiba Awad.

In 2020, during the preparation of the ANR SeMaFoR project, we started a cooperation with Alterway/Smile, an SME specialized in Cloud and DevOps technologies. This cooperation resulted in a joint PhD thesis (called Cifre) entitled "A model-based approach for dynamic, multi-scale distributed systems" started in Nov. 2021.

The first publication to emerge from this collaboration will be presented at next year's SAC conference 15.

OVHcloud

Participants: Yasmina Bouziem, Helene Coullon, Thomas Ledoux, Pierre Jacquet.

In 2021, INRIA and OVHcloud have signed an agreement to jointly study the problem of a more frugal Cloud. They have identified 3 axes : (i) Software eco-design of Cloud services and applications; (ii) Energy efficiency leverages; (iii) Impact reduction and support for Cloud users. The Stack team obtained a PhD grant and a 24-month post-doc grant.

Pierre Jacquet started his PhD in October 2021, under a co-supervision with the Spirals team with the subject "Fostering the Frugal Design of Cloud Native Applications". Pierre presented a poster, ”Sampling Resource Requirements to Optimize Virtual Machines Sizing”, at the EuroSys conference in April 2022.

Yasmina Bouziem started her postdoc in September 2022 for two years, under a co-supervision with the Avalon team in Lyon with the subject "pulling the energy cost of a reconfiguration execution within reconfiguration decisions".

Orange

Participants: Paul Bori, Divi de Lacour, Adrien Lebre, Thomas Ledoux, Dan Freeman Mahoro, Jean-Marc Menaud, Duc-Thinh Ngo, Kandaraj Piamrat, Mario Südholt.

Since 2022, Orange Labs and the Stack team have been launched several PhD grants.

Dan Freeman Mahoro has initiated a new collaboration on the theme of "digital twins". This cooperation has led to a joint doctoral thesis entitled "Digital twins of complex cyber-physical systems", which began in April 2022, co-supervised with the Orange team in Rennes, and has a first publication 26. However, Dan Freeman Mahoro stopped his PhD for several reasons in October, preferring to join the industry as an engineer.

Paul Bori started his PhD in January 2023, with the subject "Container application security: a programmable OS-level approach to monitoring network flows and process executions".

Duc-Thinh Ngo started his PhD in December 2022, on the subject "Dynamic graph learning algorithms for the digital twin in edge-cloud continuum", under a co-supervision with Orange team in Rennes.

Divi de Lacour started his PhD in January 2022, on the subject "Architecture et services pour la protection des données poursy stèmes coopératifs autonomes", under a co-supervision with the Orange team in Chatillon (Paris south region).

Ericsson

Participants: Samia Boutalbi, Mario Südholt, Remous-Aris Koutsiamanis.

Samia Boutalbi started her PhD in January 2022, on the subject "Secure deployment of micro-services in a shared Cloud RAN/MEC environment", under a co-supervision with the Ericsson team in Paris.

10.1.1 Visits of international scientists

10.2.1 Horizon Europe

10.2.2 Other european programs/initiatives

10.3.1 ANR

10.3.2 PIA 4

10.3.3 CPER

10.3.4 Local and regional projects

10.3.5 Inria Challenges

11.1.1 Scientific events: organisation

11.1.2 Scientific events: selection

11.1.3 Journal

11.1.4 Invited talks

• Thomas Ledoux: SIF (Société Informatique de France) annual conference : "Frugalité numérique : vers une approche holistique et centrée sur l'humain pour les systèmes distribués"
• Daniel Balouek: Distributed Computing Continuum (DCC) at IEEE Cloud 2023 : "Leveraging the Computing Continuum for Urgent Science"
• Adrien Lebre: Cloud Computing lecture at the RSD Winter school (France)

11.1.5 Leadership within the scientific community

• Helene Coullon is co-chair of the working group YODA (trustworthY and Optimal Dynamic Adaptation) in the national GDR GPL (software engineering and languages)
• Helene Coullon is co-chair of the working group CyclOps (DevOps, deployment and reconfiguration, lifecycle etc.) in the joint laboratory between Inria and Orange
• Helene Coullon is Vice-president of the French ACM SIGOPS group

11.1.6 Scientific expertise

• Jacques Noyé has acted as a reviewer for the Swiss National Science Foundation.
• Remous-Aris Koutsiamanis has acted as a reviewer for the National Science Centre Poland.
• Daniel Balouek has acted as a reviewer for the USA National Science Foundation.

11.1.7 Research administration

• Adrien Lebre : Member of the executive committee of the Grid’5000 GIS (Groupement d’intérêt scientifique), Member of the SLICES-FR temporary executive board, Co-director of the <I/O> Lab, a joint lab between Inria and Orange Labs, co-leader the French CLOUD PEPR, and since December 2023, head of the Cloud, Network and System program at Inria.
• Kandaraj Piamrat is international coordinator of LS2N (Laboratoire des sciences du numérique de Nantes).
• Jean-Marc Menaud is deputy head of LS2N (Laboratoire des sciences du numérique de Nantes)
• Remous-Aris Koutsiamanis : Member of the executive committee of the Grid’5000 GIS (Groupement d’intérêt scientifique), Member of the SLICES-FR temporary executive board, Member of the SLICES-FR Architects committee, Member of the SLICES-FR Architects committee, Member of the SLICES-FR Site managers, Scientific representative of IMT to SLICES.

11.2.1 Teaching

As a team mainly composed of Associate Prof. and Prof., the amount of teaching activities is significant (around 150hours per person). We present here only the management activities.

• Hélène Coullon : responsible for the LOGIN training in computer science at IMT Atlantique (last year)
• Adrien Lebre : responsible for the FISE research program at IMT Atlantique (Nantes campus).
• Thomas Ledoux : head of the apprenticeship program in Software Engineering FIL. This 3-year program leads to the award of a Master degree in Software Engineering from the IMT Atlantique.
• Thomas Ledoux: member of the teaching committee at IMT Atlantique
• Thomas Ledoux: co-pilot of the redesign of the common core of the 1st year of the IT curriculum at IMT Atlantique
• Thomas Ledoux : head of the Filière informatique nantaise since Sept. 2020. This entity, created by the University of Nantes, Centrale Nantes and IMT Atlantique, aims to bring together the main players in Computer Science training in Nantes to ensure a coherent and ambitious training offer that meets the present and future challenges of Computer Science. It is organized around a Council made up of representatives from the academic and socio-economic worlds.
• Thomas Ledoux : member of the board of directors of Talents du numérique.
• Jacques Noyé : deputy head of the Automation, Production and Computer Sciences Department of IMT Atlantique.
• Mario Südholt : representative for MSc-level and PhD-level studies of the API department of IMT Atlantique.
• Mario Südholt : coordinator of the international PhD program SEED.
• Kandaraj Piamrat : elected member of scientific council at Faculty of Sciences and Techniques, Nantes University
• Kandaraj Piamrat : responsible for Licence MIAGE, CS Department, Nantes University

11.2.2 Supervision

• PhD: Marie Delavergne, Cheops, a service-mesh to geo-distribute micro-service applications at the Edge 27, Sept 2019 - March 2023, Director: A. Lebre.
• PhD: Wilmer Garzon, Secure distributed workflows for biomedical data analytics, Sept 2019 - Jan 2023, Director: M. Südholt, Advisor: D. Benavides.
• PhD in progress: Geo Johns Antony, Resource management in geo-distributed infrastructures: the Kubernetes case, April 2021 - Sept 2024, Director: A. Lebre.
• PhD in progress: Samia Boutalbi, Secure deployment of microsservices in a shared RAN/MEC Cloud environment, Jan 2022 - Jan 2025, Director: M. Südholt, Advisor: R.-A. Koutsiamanis.
• PhD in progress: Abdou Seck, Parallel transfer service for the exchange of large volumes of data between Datacenters, June 2022 - June 2025, Director: J.-M. Menaud, Noel De Palma, Advisor: R.-A. Koutsiamanis.
• PhD in progress: Pierre Jacquet, Fostering the Frugal Design of Cloud Native Applications, Oct 2021 - Oct 2024, Director R. Rouvoy (SPIRALS Lille), Advisor: T. Ledoux.
• PhD in progress: Hiba Awad, A Model-based Approach for Multi-Scale and Dynamic Distributed Systems, Nov. 2021 - March 2025. Director: T. Ledoux.
• PhD in progress: Antoine Omond, Safe, efficient and low-energy self-adaptation for Cyber Physical Systems - Application to a scientific observatory in the Arctic tundra, Dec 2021 - Dec 2024. Director: T. Ledoux, Advisor: H. Coullon.
• PhD in progress: Dan Freeeman Mahoro, Digital twins of complex cyber-physical systems, Apr. 2022 - March 2025, Director: T. Ledoux.
• PhD in progress: Duc Thinh Ngo, Dynamic graph learning algorithms for the digital twin in edge-cloud continuum, Dec.2022 - Nov.2025, Director: A. Lebre, Advisor:: K. Piamrat
• PhD in progress: Tengfei An, Modeling and Studying Self-Stabilization within Kubernetes, Nov 2023 - Sept 2026, Director: A. Lebre, Advisors: H. Coullon, J. Noyé
• PhD in progress: Divi De Lacour, "Architecture et services pour la protection des données poursy stèmes coopératifs autonomes", Jan 2022 - Dec 2025, Director: M. Südholt.
• Post-doc: Yasmina Bouizem, Measure and model the energy consumption of the procedures of deployment and reconfiguration at OVH, Sept 2022 - Sept 2023, Advisor: H. Coullon.
• Post-doc: Eloi Perdereau, Configuration languages, OTPaaS, Sept 2022 - March 2024, Advisor: J. Noyé.
• Post-doc: Ons Aouedi, Advanced AI for infrastructures and applications in the IoT-Cloud continuum, Jan.- Nov. 2023, Advisor: K. Piamrat, M. Südholt
• Post-doc: Farid Arfi, Safety of decentralized reconfigurations, Feb. 2023 - Aug. 2024, Advisor: H. Coullon
• Post-doc: Tayeb Diab, Decentralized AI for the continuum Cloud-Edge-IoT, Nov. 2022-Apr. 2024, Advisor: M. Südholt
• Post-doc: Jabran Khan, Placement in Cloud, Edge and Far Edge devices in the IoT to Cloud continuum, Feb. 2023 - Jul. 2024, Advisor: R.-A. Koutsiamanis, J.-M. Menaud
• Post-doc: Anas Mokhtari, A Holistic Approach for Designing Carbon-Aware and Energy-Aware Cloud applications, Sept. 2023 - Aug. 2024, Advisor: T. Ledoux.
• Post-doc: Clément Mommessin, Model of Energy consumption in Cloud, Edge and Far Edge devices in the IoT to Cloud continuum, Jan. 2023 - Jun. 2024, Advisor: J.-M. Menaud, R.-A. Koutsiamanis
• Post-doc: Jolan Philippe, Decentralization of distributed systems reconfiguration by using constraint programming, Feb. 2023 - Aug. 2024, Advisor: H. Coullon

11.2.3 Juries

• Kandaraj Piamrat and Helene Coullon were members of the selection commitee for an associate professor positions in Rennes.
• Kandaraj Piamrat was an examinator of Sabra Ben Saad Thesis - Security architectures for network slice management for 5G and beyond. EURECOM, 02/23.
• Kandaraj Piamrat was an examinator of Mustafa Al Samara Thesis - Network Anomaly Detection in IoT: from Data Efficiency to Enhancing QoS, 06/23.
• Helene Coullon was member of the selection committee for research positions at Centre Inria de l'Université de Rennes
• Helene Coullon was an examinator of the PhD defense of Edouard Guégain at Université de Lille - Configuration-driven Software Optimization, 2023-09-29
• Helene Coullon was an examinator of the PhD defense of Davaadorj Battulga at Université de Rennes 1 - Contributions to the Management of Stream Processing Pipelines in Fog Computing Environments, 2023-03-23
• Adrien Lebre was a reviewer for the PhD thesis of Nihel Kaboubi, “Système de partitionnement hybride pour une inférence distribuée et embarquée des CNNs sur les équipements en bordure de réseau”, Université de Grenoble Alpes, March 2023
• Adrien Lebre was reviewer for the Phd Thesis of Thomas Feltin, “Distributed Computing at the Smart Device Edge”, Ecole Doctorale de l’Institut Polytechnique de Paris, Dec 2023
• Thomas Ledoux was member of the selection commitee for an associate professor position in IMT Atlantique
• Thomas Ledoux was chairman of the PhD thesis jury of Marie Delavergne ("Cheops, a service-mesh to geo-distribute micro-service applications at the Edge") 27, 2023-03-16
• Jean-Marc Menaud was member of the selection commitee for two associate professor positions in Toulouse and Lyon.

11.3.1 Articles and contents

• Adrien Lebre - "Quèsaco le cloud  ?", www.imt-atlantique.fr/fr/actualites/quesaco-le-cloud
• Thomas Ledoux - "La chasse au gaspillage dans le cloud et les data centers.", The Conversation, January 2023 30

11.3.2 Education

Thomas Ledoux was co-leader of the Ecolog initiative. This national project is the result of an association between the Institut du Numérique Responsable (INR) and the IT sector in Nantes, which includes the University of Nantes, IMT Atlantique and Centrale Nantes. Its ambition was to create a body of training courses available in open source and dedicated to sustainable computing. A webinar presenting the results was held on March 23, 2023 (ecolog.isit-europe.org).

11.3.3 Interventions

Thomas Ledoux took part in a round table related to digital sustainability/green computing organized by ADN Ouest (Nov. 14, 2023).

International journals

• 6 articleA.Abdelghani Alidra, H.Hugo Bruneliere and T.Thomas Ledoux. A feature-based survey of Fog modeling languages.Future Generation Computer Systems138January 2023, 104-119HALDOIback to textback to text
• 7 articleO.Ons Aouedi and K.Kandaraj Piamrat. F-BIDS: Federated-Blending based Intrusion Detection System.Pervasive and Mobile Computing892023, 101750HALDOIback to textback to text
• 8 articleY.Yasmina Bouizem, D.Djawida Dib, N.Nikos Parlavantzas and C.Christine Morin. Integrating request replication into FaaS platforms: an experimental evaluation.Journal of Cloud Computing: Advances, Systems and Applications121June 2023, 1-20HALDOI
• 9 articleH.Hélène Coullon, L.Ludovic Henrio, F.Frédéric Loulergue and S.Simon Robillard. Component-Based Distributed Software Reconfiguration: a Verification-Oriented Survey.ACM Computing Surveys561May 2023, 1-37HALDOIback to textback to textback to text
• 10 articleD.-T.Duc-Thinh Ngo, O.Ons Aouedi, K.Kandaraj Piamrat, T.Thomas Hassan and P.Philippe Raipin-Parvédy. Empowering Digital Twin for Future Networks with Graph Neural Networks: Overview, Enabling Technologies, Challenges, and Opportunities.Future internet1512November 2023, 377HALDOIback to text
• 11 articleV.Vasileios Perifanis, N.Nikolaos Pavlidis, R.-A.Remous-Aris Koutsiamanis and P.Pavlos Efraimidis. Federated learning for 5G base station traffic forecasting.Computer Networks2351389-1286August 2023, 109950HALDOIback to textback to textback to text

Invited conferences

• 12 inproceedingsD.Divi De Lacour, M.Marc Lacoste, M.Mario Südholt and J.Jacques Traoré. Towards Scalable Resilient Federated Learning: A Fully Decentralised Approach.PeRConAI 2023: 2nd IEEE Workshop on Pervasive and Resource-constrained Artificial IntelligenceAtlanta (GA), United StatesIEEE2023HALDOI

International peer-reviewed conferences

• 13 inproceedingsA.Abdelghani Alidra, H.Hugo Bruneliere, H.Hélène Coullon, T.Thomas Ledoux, C.Charles Prud'Homme, J.Jonathan Lejeune, P.Pierre Sens, J.Julien Sopena and J.Jonathan Rivalan. SeMaFoR - Self-Management of Fog Resources with Collaborative Decentralized Controllers.SEAMS 2023 - IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing SystemsMelbourne, AustraliaIEEEMay 2023, 25-31HALDOIback to text
• 14 inproceedingsO.Ons Aouedi, K.Kandaraj Piamrat and M.Mario Südholt. HFedSNN: Efficient Hierarchical Federated Learning using Spiking Neural Networks.MobiWac 2023: 21st ACM International Symposium on Mobility Management and Wireless AccessMontréal, CanadaSeptember 2023HALback to text
• 15 inproceedingsH.Hiba Awad, A.Abdelghani Alidra, H.Hugo Bruneliere, T.Thomas Ledoux, E.Etienne Leclerq and J.Jonathan Rivalan. VeriFog: A Generic Model-based Approach for Verifying Fog Systems at Design Time.The 39th ACM/SIGAPP Symposium on Applied Computing (SAC ’24)The 39th ACM/SIGAPP Symposium on Applied Computing (SAC ’24)Avila, SpainApril 2024HALDOIback to textback to text
• 16 inproceedingsD.Daniel Balouek and H.Hélène Coullon. Dynamic Adaptation of Urgent Applications in the Edge-to-Cloud Continuum.International European Conference on Parallel and Distributed Computing (Euro-Par'2023)Limassol, CyprusAugust 2023HALback to text
• 17 inproceedingsD.Daniel Balouek, I.Ismael Perez, S. D.Sam D Faulstich, H. A.Heather A Holmes, I.Ilkay Altintas and M.Manish Parashar. Keynote Talk: Leveraging the Edge-Cloud Continuum to Manage the Impact of Wildfires on Air Quality.2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)Atlanta, FranceIEEEMarch 2023, 27-31HALDOIback to text
• 18 inproceedingsS.Samia Boutalbi, N.Nizar Kheir, R. A.Remous Aris Koutsiamanis, M.Mario Südholt and Y.Yann Dan Moussa. Mobile Edge Slice Broker: Mobile Edge Slices Deployment in Multi-Cloud Environments.ICFEC 2023 - 7th IEEE International Conference on Fog and Edge ComputingBangalore, India2023, 1-6HALback to text
• 19 inproceedingsP.Pierre Jacquet, T.Thomas Ledoux and R.Romain Rouvoy. CLOUDFACTORY: An Open Toolkit to Generate Production-like Workloads for Cloud Infrastructures.IC2E 2023 - 11th IEEE International Conference on Cloud EngineeringBoston, Massachusetts, USA, United StatesIEEESeptember 2023, 1-11HALback to text
• 20 inproceedingsA.Antoine Omond, H.Hélène Coullon, I.Issam Raïs and O.Otto Anshus. Leveraging Relay Nodes to Deploy and Update Services in a CPS with Sleeping Nodes.Proceeding of the 2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)CPSCom 2023 - 16th IEEE International Conference on Cyber, Physical and Social ComputingHainan Island, ChinaIEEEDecember 2023, 1-8HALback to text
• 21 inproceedingsA.Antoine Omond, I.Issam Raïs and H.Hélène Coullon. Evaluating the energy consumption of adaptation tasks for a CPS in the Arctic Tundra.Proceeding of the 2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)GreenCom 2023 - 9th IEEE International Conference on Green Computing and CommunicationsHainan Island, ChinaIEEE2023, 1-8HALback to text
• 22 inproceedingsV.Vasileios Perifanis, N.Nikolaos Pavlidis, S.Selim Yilmaz, F.Francesc Wilhelmi, E.Elia Guerra, M.Marco Miozzo, P.Pavlos Efraimidis, P.Paolo Dini and R.-A.Remous-Aris Koutsiamanis. Towards Energy-Aware Federated Traffic Prediction for Cellular Networks.2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC)FMEC 2023 - Eighth International Conference on Fog and Mobile Edge Computing (FMEC)Tartu, EstoniaIEEE2023, 93-100HALDOIback to text
• 23 inproceedingsS.Shahrzad Pour, D.Daniel Balouek, A.Amir Masoumi and M.Martin Brynskov. An urgent computing oriented architecture for dynamic climate risk management framework.International Workshop on Intelligent and Adaptive Edge-Cloud Operations and Services (Intel4EC 2023)Taormina, ItalyDecember 2021HALback to text
• 24 inproceedingsC.Christian Sicari, D.Daniel Balouek, M.Massimo Villari and M.Manish Parashar. Event-Driven FaaS Workflows for Enabling IoT Data Processing at the Cloud Edge Continuum.International Conference on Utility and Cloud Computing (UCC 2023)Taormina, Italy2023HALback to textback to text
• 25 inproceedingsC.Christian Sicari, A.Alessio Catalfamo, L.Lorenzo Carnevale, A.Antonino Galletta, D.Daniel Balouek, M.Manish Parashar and M.Massimo Villari. TEMA: Event Driven Serverless Workflows Platform for Natural Disaster Management.2023 IEEE Symposium on Computers and Communications (ISCC)Gammarth, FranceIEEEJuly 2023, 1-6HALDOIback to text

Conferences without proceedings

• 26 inproceedingsD. F.Dan Freeman Mahoro, T.Thomas Ledoux, T.Thomas Hassan and T.Thierry Coupaye. Articulating Data and Control Planes for the Composition and Synchronization of Digital Twins.Midd4DT 2023 - 1st International Workshop on Middleware for Digital TwinBologna (ITALY), ItalyACMDecember 2023, 13-18HALDOIback to text

Doctoral dissertations and habilitation theses

• 27 thesisM.Marie Delavergne. Cheops, a service-mesh to geo-distribute micro-service applications at the Edge.Ecole nationale supérieure Mines-Télécom AtlantiqueMarch 2023HALback to textback to text
• 28 thesisW.Wilmer Garzón-Alfonso. Secure distributed workflows for biomedical data analytics.Ecole nationale supérieure Mines-Télécom Atlantique; Escuela Colombiana de Ingeniería Julio GaravitoAugust 2023HALback to text

Other scientific publications

• 29 miscE.Eloi Perdereau and J.Jacques Noyé. The LIFE of CUE.October 2023HALback to text

Scientific popularization

• 30 articleP.Pierre Jacquet, R.Romain Rouvoy and T.Thomas Ledoux. La chasse au gaspillage dans le cloud et les data centers.The ConversationJanuary 2023HALback to text