DESCRIPTION :
Define, implement, and evaluate agentic behaviors for distributed edge nodes, leveraging scalable experiments on the Grid'5000 testbed and algorithmic insights from Edge-Cloud operations, incorporating:
* Survey Edge Intelligence operations such as computation offloading, data pipelines and on-edge learning to extract key algorithmic techniques and metrics.
* Define agentic AI behaviors (state, actions, reward) suitable for edge resource management;
* Develop agentic policy models using reinforcement learning (RL) or multi-agent reinforcement learning (MARL) to autonomously decide:
* when and where to offload tasks,
* how to allocate resources,
* how to adapt to network variability
4. Evaluate:
* Latency and throughput improvements over baseline strategies.
* Energy/CPU utilization and stability under load.
* Agent adaptability to changing workloads & link conditions
References
Daniel Balouek-Thomert, Ivan Rodero, and Manish Parashar. Harnessing the computing continuum for urgent science. SIGMETRICS Perform. Eval. Rev., 48(2) :41-46, November 2020.
Zhang, Ruichen, Guangyuan Liu, Yinqiu Liu, Changyuan Zhao, Jiacheng Wang, Yunting Xu, Dusit Niyato et al. "Toward edge general intelligence with agentic AI and agentification: Concepts, technologies, and future directions." arXiv preprint arXiv:2508.18725 (2025).
S. Ilager et al., "Proteus: Towards Intent-driven Automated Resource Management for Edge Sensor Nodes," in 14th Workshop on AI and Scientific Computing, 2024.
Compétences
Cloud Computing, Edge Computing, Distributed systems
Python, Docker/Kubernetes
Code d'emploi : Ingénieur en Intelligence Artificielle (h/f)
Domaine professionnel actuel : IT R&D Professionals
Niveau de formation : Bac+4
Temps partiel / Temps plein : Plein temps
Type de contrat : Stage/Jeune diplômé
Compétences : Intelligence Artificielle, Cloud Computing, Informatique Distribuée, Python (Langage de Programmation), Informatique Scientifique, Apprentissage par Renforcement, Multi-Agent Systems, Kubernetes, Pipeline de Données, Docker, Anglais, Adaptabilité, Prise de Décision, Curiosité, Systèmes Automatisés, Expérimentation, Gestion des Ressources, Banc d'Essai, Déchargement, Métrique, Capteurs, Réalisation de Diagrammes
Courriel :
Daniel.Balouek@inria.fr
Téléphone :
0139635511
Type d'annonceur : Employeur direct