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Computer Science > Networking and Internet Architecture

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By Jernej Hribar, Maice Costa
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2507.07671] Multi-agent Reinforcement Learning-based In-place Scaling Engine for Edge-cloud Systems

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By Carolina Fortuna, Shih-Kai Chou, Ramon Sanchez-Iborra, Jernej Hribar
| arXiv
[Submitted on 10 Jul 2025] Title:Multi-agent Reinforcement Learning-based In-place Scaling Engine for Edge-cloud Systems View a PDF of the paper titled Multi-agent Reinforcement Learning-based In-place Scaling Engine for Edge-cloud Systems, by Jovan Prodanov and 5 other authors View PDF HTML (experimental) Abstract:Modern edge-cloud systems face challenges in efficiently scaling resources to handle dynamic and unpredictable workloads.
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