TY  - RPRT
A1  - Dworzak, Manuel
A1  - Großmann, Marcel
A1  - Le, Duy Thanh
T1  - Federated Learning for Service Placement in Fog and Edge Computing
T2  - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23)
N2  - Service orchestration requires enormous attention and is a struggle nowadays. Of course, virtualization provides a base level of abstraction for services to be deployable on a lot of infrastructures. With container virtualization, the trend to migrate applications to a micro-services level in order to be executable in Fog and Edge Computing environments increases manageability and maintenance efforts rapidly. Similarly, network virtualization adds effort to calibrate IP flows for Software-Defined Networks and eventually route it by means of Network Function Virtualization. Nevertheless, there are concepts like MAPE-K to support micro-service distribution in next-generation cloud and network environments. We want to explore, how a service distribution can be improved by adopting machine learning concepts for infrastructure or service changes. Therefore, we show how federated machine learning is integrated into a cloud-to-fog-continuum without burdening single nodes.
KW  - fog computing
KW  - SDN
KW  - orchestration
KW  - federated learning
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322193
ER  -