Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Adaptive Vertical Pod Autoscaler for Efficient Cloud Computing Resource Utilization based on Bi-LSTM

Full metadata record
DC Field Value Language
dc.contributor.author정영식-
dc.date.accessioned2023-05-11T10:41:25Z-
dc.date.available2023-05-11T10:41:25Z-
dc.date.issued2021-12-15-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/11734-
dc.titleAdaptive Vertical Pod Autoscaler for Efficient Cloud Computing Resource Utilization based on Bi-LSTM-
dc.typeConference-
dc.citation.conferenceNameThe 13th International Conference on Computer Science and its Applications (CSA 2021)-
dc.citation.conferencePlace대한민국-
dc.citation.conferencePlace메종글래드호텔-
dc.citation.conferenceDate2021-12-15 ~ 2021-12-17-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 2. Conference Papers

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Jeong, Young Sik photo

Jeong, Young Sik
College of Advanced Convergence Engineering (Department of Computer Science and Artificial Intelligence)
Read more

Altmetrics

Total Views & Downloads

BROWSE