Acknowledgement
This work was supported by Electronics and Telecommunications Research Institute (ETRI) grant funded by the Korean government. [21ZS1300, Research on High Performance Computing Technology to overcome limitations of AI processing]
References
- TTA, Keyword: Edge Device. [Internet]. Available: http://terms.tta.or.kr/main.do.
- H. J. Choi, B. G. Ko, J. S. Lee, E. S. Kang, J. O. Kim, and B. K. Lee, "Optimization function analysis for tower AI learning," in Proceeding of Journal of Korea Society of Computer Information, Jeju, Korea, vol. 28, no. 2, pp. 351-353, 2020.
- J. W. Park and Y. B. Ko, "A Lightweight CNN Algorithm based on Explainable AI for UWB Localization in Disaster Environments," in Proceedings of Korean Institute of Next Generation Computing, Gwangju, Korea, pp. 30-33, 2021.
- I. G. Chun, S. J. Kang, and G. J. Na, "EdgeCPS Technology Trend for Massive Autonomous Things," Electronics and Telecommunications Trends, vol. 37, no. 1, pp. 32-41, Nov. 2021. https://doi.org/10.22648/ETRI.2022.J.370104
- Y. J. Kim, I. G. Chun, S. J. Kang, G. N. Na, Y. Y. Kim, J. H. Jeon, and J. H. Lee, "A Design Plan for Constructing the Knowledge Sharing Middleware based on EdgeCPS for Harmonious Execution of AI Applications)," in Proceeding of The 16th IEMEK Symposium on Embedded Technology, Jeju, South Korea, pp. 210-213, 2021.
- Kubernetes Federation [Internet]. Avaiable: https://github.com/kubernetes-sigs/kubefed.
- Y. S. Kim and Y. H, Kim, "A Case Study of Orchestration for Kubernetes based Multi-Cluster," in Proceeding of the KICS Winter Conference, Pyeongchang, South Korea, pp. 153-154, 2021.
- Kubeflow [Internet]. Available: kubeflow.org.
- Y. J. Kim, G. J. Na, and I. G. Chun, "A Performance Test for Supporting Microservice of AI Applications," in Proceeding of The 17th IEMEK Symposium on Embedded Technology, Jeju, South Korea, pp. 307-310, 2022.