(Français) Projet TARANIS

Model, Deploy, Orchestrate, and Optimize Cloud Applications and Infrastructure

— Preview

Strategy based on a significant abstraction of the application structure description, in order to further automate application and infrastructure management.

Christian Perez, Inria Research Director

Keywords : Cloud, Edge, IoT, Computation Continuum, model, verification, deployment, reconfiguration, orchestrator, optimisatin

Missions
Publications
Partners
Project website

New infrastructures, such as Edge Computing or the Cloud-Edge-IoT computing continuum, make cloud issues even more complex, as they add new challenges linked to the diversity and heterogeneity of resources (from small sensors to data centers/HPCs, from low-power networks to core networks), geographical distribution, as well as increased requirements for dynamicity and security, all under constraints such as energy consumption.

To exploit these new infrastructures efficiently, the Taranis project is based on a strategy aimed at abstracting the description of the structure of applications and resources in order to automate their management even further. In this way, it will be possible to globally optimize the resources used with regard to multi-criteria objectives (price, deadline, performance, energy, etc.) on both the user side (applications) and the resource provider side (infrastructures). Taranis also addresses the challenges of abstracting application reconfiguration and dynamically adapting resource usage.

— Missions

— Our researches

The Taranis project addresses this issue via four scientific work packages, each focusing on a phase of the application lifecycle: application description model and infrastructure, deployment and reconfiguration, orchestration and optimization. Work package 0 is dedicated to project management.

Modeling

Investigate the complexity of Cloud-Edge application and infrastructure models

Deployment and reconfiguration

Investigates deployment and reconfiguration issues

Orchestration of services and resources

Extend orchestrators for the Cloud-Edge-IoT continuum

Optimization

Revisit optimization issues associated with the use of Cloud-Edge-IoT infrastructures.

— Partners

Consortium

Inria, CNRS, IMT, UGA, CEA, Université de Rennes, ENS Lyon, Université Claude Bernard Lyon 1, Université de Lille, INSA Rennes

— Research team

48 permanent staff (not funded by the project)
46 people funded by the project, including:
27 PhD students
7 post-docs
12 engineers

Our teams in France

— Publications


6 documents

Journal articles1 document

  • Fatima Elhattab, Sara Bouchenak, Cédric Boscher. PASTEL: Privacy-Preserving Federated Learning in Edge Computing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2024, 7 (4), pp.1-29. ⟨10.1145/3633808⟩. ⟨hal-04394133⟩

Conference papers4 documents

  • Brell Peclard Sanwouo, Clément Quinton, Paul Temple. Breaking the Loop: AWARE is the new MAPE-K. FSE'25 - ACM International Conference on the Foundations of Software Engineering, Jun 2025, Trondheim, Norway. ⟨hal-04992342⟩
  • Dominik Huber, Sergio Iserte, Martin Schreiber, Antonio J. Peña, Martin Schulz. Bridging the Gap Between Genericity and Programmability of Dynamic Resources in HPC. ISC High Performance 2025 - 40th ISC High Performance International Conference, Jun 2025, Hamburg, Germany. pp.1-11. ⟨hal-04994828⟩
  • Cédric Boscher, Nawel Benarba, Fatima Elhattab, Sara Bouchenak. Personalized Privacy-Preserving Federated Learning. Proceedings of the 25th International Middleware Conference, Dec 2024, Hong Kong, China. pp.454--466, ⟨10.1145/3652892.3700785⟩. ⟨hal-04770214⟩
  • Yasmine Djebrouni, Isabelly Rocha, Sara Bouchenak, Lydia Chen, Pascal Felber, et al.. Characterizing Distributed Machine Learning Workloads on Apache Spark. Middleware '23: 24th International Middleware Conference, Dec 2023, Bologna, Italy. pp.151-164, ⟨10.1145/3590140.3629112⟩. ⟨hal-04399409⟩

Other publications1 document


Powered by HAL logo

Other projects

CARECloud

Understanding, improving and reducing the environmental impact of cloud computing

Read more

Archi-CESAM

Efficient and safe converged architecture based on near-memory gas pedals / Archi-CESAM

Read more

DiVa

Virtualized disaggregation

Read more

Taranis

Model, deploy, orchestrate and optimize cloud applications and infrastructures

Read more

PEPR Cloud projects

Spirec

Multi-level supervision and prediction for geo-distributed and heterogeneous infrastructures in the Cloud/Edge/IoT continuum

Read more

Steel

Efficient and secure data storage and processing on cloud-based infrastructures

Read more

Silecs

Super Infrastructure for Large-Scale Experimental Computer Science for Cloud/Edge/IoT

Read more

TrustinCloudS

Cloud infrastructure security

Read more

Comments are closed.