Publications

Main Publication

E2Clab Optimization

E2Clab Provenance

Other Publications (using or citing E2Clab)

  • Daniel Rosendo, Alexandru Costan, Patrick Valduriez, Gabriel Antoniu. Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review. Journal of Parallel and Distributed Computing, Elsevier, 2022, 166, pp.71-94.

  • Daniel Rosendo, Kate Keahey, Alexandru Costan, Matthieu Simonin, Patrick Valduriez, et al.. KheOps: Cost-effective Repeatability, Reproducibility, and Replicability of Edge-to-Cloud Experiments. ACM REP 2023 - Conference on Reproducibility and Replicability, Jun 2023, Santa Cruz, CA, United States. pp.62-73.

  • Zeina Houmani, Daniel Balouek-Thomert, Eddy Caron, Manish Parashar. Enabling microservices management for Deep Learning applications across the Edge-Cloud Continuum. SBAC-PAD 2021 - IEEE 33rd International Symposium on Computer Architecture and High Performance Computing, Oct 2021, Belo Horizonte, Brazil. pp.1-10, ⟨https://hal.archives-ouvertes.fr/hal-03409405⟩.

  • Daniel Balouek-Thomert, Pedro Silva, Kevin Fauvel, Alexandru Costan, Gabriel Antoniu, et al.. MDSC: Modelling Distributed Stream Processing across the Edge-to-Cloud Continuum. DML-ICC 2021 workshop (held in conjunction with UCC 2021), Dec 2021, Leicester, United Kingdom. ⟨https://hal.archives-ouvertes.fr/hal-03510012⟩

  • Davaadorj Battulga, Daniele Miorandi, Cédric Tedeschi. SpecK: Composition of Stream Processing Applications over Fog Environments. DAIS 2021 - 21st International Conference on Distributed Applications and Interoperable Systems, Jun 2021, Valetta, Malta. pp.38-54, ⟨https://hal.archives-ouvertes.fr/hal-03259975⟩.

  • Thomas Bouvier, Alexandru Costan, Gabriel Antoniu. Deploying Heterogeneity-aware Deep Learning Workloads on the Computing Continuum. BDA 2021 - 37e Conférence sur la Gestion de Données - Principes, Technologies et Applications, Oct 2021, Paris, France. ⟨https://hal.archives-ouvertes.fr/hal-03338520⟩

  • Ronan-Alexandre Cherrueau, Marie Delavergne, Alexandre van Kempen, Adrien Lebre, Dimitri Pertin, et al.. EnosLib: A Library for Experiment-Driven Research in Distributed Computing. IEEE Transactions on Parallel and Distributed Systems, Institute of Electrical and Electronics Engineers, In press. ⟨https://hal.archives-ouvertes.fr/hal-03324177/⟩

  • Cédric Prigent, Loïc Cudennec, Alexandru Costan, Gabriel Antoniu. A Methodology to Build Decision Analysis Tools Applied to Distributed Reinforcement Learning. ScaDL 2022 - Scalable Deep Learning over Parallel and Distributed Infrastructures - An IPDPS Workshop, Jun 2022, Lyon / Virtual, France. pp.1-10. ⟨https://hal.archives-ouvertes.fr/hal-03613558⟩

  • Cédric Prigent, Alexandru Costan, Gabriel Antoniu, Loïc Cudennec. Enabling Federated Learning across the Computing Continuum: Systems, Challenges and Future Directions. Future Generation Computer Systems, 2024, 160, pp.767-783. <https://hal.science/hal-04659211>

  • Cédric Prigent, Melvin Chelli, Alexandru Costan, Loïc Cudennec, René Schubotz, et al.. Efficient Resource-Constrained Federated Learning Clustering with Local Data Compression on the Edge-to- Cloud Continuum. HiPC 2024 - 31st IEEE International Conference on High Performance Computing, Data, and Analytics, Dec 2024, Bengaluru (Bangalore), India. pp.1-11. <https://hal.science/hal-04779813>

  • Melvin Chelli, Cédric Prigent, René Schubotz, Alexandru Costan, Gabriel Antoniu, et al.. FedGuard: Selective Parameter Aggregation for Poisoning Attack Mitigation in Federated Learning. Cluster 2023 - IEEE International Conference on Cluster Computing, Oct 2023, Santa Fe, New Mexico, United States. pp.1-10. <https://hal.science/hal-04208787>

  • Mathis Valli, Alexandru Costan, Cédric Tedeschi, Loïc Cudennec. Towards Efficient Learning on the Computing Continuum: Advancing Dynamic Adaptation of Federated Learning. FlexScience 2024 - 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures, Jun 2024, Pisa, Italy. pp.42-49. <https://hal.science/hal-04698619>