A Multi-Agent Deep-Reinforcement Learning Approach for Application-Agnostic Microservice Scaling

Fodor, Balázs and Jakub, Ákos and Szűcs, Gábor and Sonkoly, Balázs (2023) A Multi-Agent Deep-Reinforcement Learning Approach for Application-Agnostic Microservice Scaling. In: 2023 IEEE Virtual Conference on Communications (VCC). IEEE, Piscataway (NJ), pp. 139-144. ISBN 9798350318807

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Official URL: https://doi.org/10.1109/VCC60689.2023.10474695

Item Type:	Book Section
Additional Information:	Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics, Department of Telecommunications and Media Informatics, Hungary MTA-BME Network Softwarization Research Group, Hungary HUN-REN-BME Cloud Applications Research Group, Hungary Conference code: 198413 Export Date: 22 April 2024
Subjects:	Q Science / természettudomány > QA Mathematics / matematika > QA76 Computer software / programozás
SWORD Depositor:	MTMT SWORD
Depositing User:	MTMT SWORD
Date Deposited:	29 Sep 2024 03:54
Last Modified:	29 Sep 2024 03:54
URI:	https://real.mtak.hu/id/eprint/206366

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