Suche nach Personen

plus im Publikationsserver
plus bei BASE
plus bei Google Scholar

Daten exportieren

 

Network-aware migration control and scheduling of differentiated virtual machine workloads

Titelangaben

Verfügbarkeit überprüfen

Stage, Alexander ; Setzer, Thomas:
Network-aware migration control and scheduling of differentiated virtual machine workloads.
In: ICSE Workshop on Software Engineering Challenges of Cloud Computing, 2009 : CLOUD '09; Vancouver, Canada, 23 May 2009. - Vancouver, Kanada, 2009. - S. 9-14
ISBN 978-1-4244-3713-9

Volltext

Volltext Link zum Volltext (externe URL):
https://doi.org/10.1109/CLOUD.2009.5071527

Kurzfassung/Abstract

Server virtualization enables dynamic workload management for data centers. However, especially live migrations of virtual machines (VM) induce significant overheads on physical hosts and the shared network infrastructure possibly leading to host overloads and SLA violations of co-hosted applications. While some recent work addresses the impact of live migrations on CPUs of physical hosts, little attention has been given to the control and optimization of migration algorithms and migration-related network bandwidth consumption. In this paper we introduce network topology aware scheduling models for VM live migrations. We propose a scheme for classifying VMs based on their workload characteristics and propose adequate resource and migration scheduling models for each class, taking network bandwidth requirements of migrations and network topologies into account. We also underline the necessity for additional migration control parameters for efficient migration scheduling.

Weitere Angaben

Publikationsform:Aufsatz in einem Buch
Institutionen der Universität:Wirtschaftswissenschaftliche Fakultät > Betriebswirtschaftslehre > ABWL und Wirtschaftsinformatik
DOI / URN / ID:10.1109/CLOUD.2009.5071527
Titel an der KU entstanden:Nein
KU.edoc-ID:24994
Eingestellt am: 06. Okt 2020 09:24
Letzte Änderung: 06. Okt 2020 16:22
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/24994/
AnalyticsGoogle Scholar