VScaler:Autonomic Virtual Machine Scaling

Publikation: Beitrag zu KonferenzenPaperBeigetragenBegutachtung

Abstract

Recent research results in cloud community found that cloud users increasingly force providers to shift from fixed bundle instance types(e.g. Amazon instances) to flexible bundles and shrinked billing cycles. This means that cloud applications can dynamically provision the used amount of resources in a more fine-grained fashion. This observation calls for approaches which are able to automatically implement fine granular VM resource allocation with respect to user-provided SLAs. In this work we propose VScaler, a framework which implements autonomic resource allocation using a novel approach to reinforcement learning.

Details

OriginalspracheEnglisch
Seiten212-219
Seitenumfang8
PublikationsstatusVeröffentlicht - 2013
Peer-Review-StatusJa

Konferenz

Titel6th IEEE International Conference on Cloud Computing
UntertitelChange we are leading
KurztitelCLOUD 2013
Veranstaltungsnummer6
Beschreibungco-located with the 9th IEEE 2013 World Congress on Services (SERVICES 2013), the 20th IEEE 2013 International Conference on Web Services (ICWS 2013), the 10th IEEE 2013 International Conference on Services Computing (SCC 2013), the 2nd IEEE 2013 International Conference on Mobile Services (MS 2013), and the 2nd IEEE 2013 International Congress on Big Data (BigData 2013)
Dauer27 Juni - 2 Juli 2013
Webseite
BekanntheitsgradInternationale Veranstaltung
StadtSanta Clara
LandUSA/Vereinigte Staaten

Externe IDs

Scopus 84897723736

Schlagworte

Forschungsprofillinien der TU Dresden

DFG-Fachsystematik nach Fachkollegium

Schlagwörter

  • Resourche Management, learning (artificial intelligence), Random access memory, Cloud computing, Adaption models, Prediction algorithms, scalability, performance, measurement