DDRM: An SLO-aware Deep Dynamic Resource Management Framework for Microservices

Loosely coupled microservice architectures have been widely adopted in cloud-native applications due to their inherent advantages in modularity, development agility, and scalability. However, the resulting complex and dynamic service topologies introduce intricate inter-service dependencies, which o...

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Podrobná bibliografia

Vydané v:	Proceedings / IEEE International Conference on Cluster Computing s. 1 - 12
Hlavní autori:	Tang, Liangping, Wang, Jin, Wang, Wanyou, Shi, Gaotao, Li, Zhijun
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 02.09.2025
Predmet:	Adaptation models Cloud computing Collaboration Deep learning deep learning for systems Dynamic scheduling Microservice architectures microservices resource efficiency resource man-agement Resource management Scalability Stability analysis Thermal stability
ISSN:	2168-9253
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