More than bin packing: Dynamic resource allocation strategies in cloud data centers. (August 2015)
- Record Type:
- Journal Article
- Title:
- More than bin packing: Dynamic resource allocation strategies in cloud data centers. (August 2015)
- Main Title:
- More than bin packing: Dynamic resource allocation strategies in cloud data centers
- Authors:
- Wolke, Andreas
Tsend-Ayush, Boldbaatar
Pfeiffer, Carl
Bichler, Martin - Abstract:
- Abstract: Resource allocation strategies in virtualized data centers have received considerable attention recently as they can have substantial impact on the energy efficiency of a data center. This led to new decision and control strategies with significant managerial impact for IT service providers. We focus on dynamic environments where virtual machines need to be allocated and deallocated to servers over time. Simple bin packing heuristics have been analyzed and used to place virtual machines upon arrival. However, these placement heuristics can lead to suboptimal server utilization, because they cannot consider virtual machines, which arrive in the future. We ran extensive lab experiments and simulations with different controllers and different workloads to understand which control strategies achieve high levels of energy efficiency in different workload environments. We found that combinations of placement controllers and periodic reallocations achieve the highest energy efficiency subject to predefined service levels. While the type of placement heuristic had little impact on the average server demand, the type of virtual machine resource demand estimator used for the placement decisions had a significant impact on the overall energy efficiency. Abstract : Highlights: We compare VM allocation strategies for cloud environments experimentally. The experiments analyze a set of 44 combinations of placement and reallocation controllers. Periodic reallocation hasAbstract: Resource allocation strategies in virtualized data centers have received considerable attention recently as they can have substantial impact on the energy efficiency of a data center. This led to new decision and control strategies with significant managerial impact for IT service providers. We focus on dynamic environments where virtual machines need to be allocated and deallocated to servers over time. Simple bin packing heuristics have been analyzed and used to place virtual machines upon arrival. However, these placement heuristics can lead to suboptimal server utilization, because they cannot consider virtual machines, which arrive in the future. We ran extensive lab experiments and simulations with different controllers and different workloads to understand which control strategies achieve high levels of energy efficiency in different workload environments. We found that combinations of placement controllers and periodic reallocations achieve the highest energy efficiency subject to predefined service levels. While the type of placement heuristic had little impact on the average server demand, the type of virtual machine resource demand estimator used for the placement decisions had a significant impact on the overall energy efficiency. Abstract : Highlights: We compare VM allocation strategies for cloud environments experimentally. The experiments analyze a set of 44 combinations of placement and reallocation controllers. Periodic reallocation has substantial impact on the overall energy efficiency. The results also show that aggressive VM placement in combination with VM reallocation strategies achieve highest efficiency. … (more)
- Is Part Of:
- Information systems. Volume 52(2015)
- Journal:
- Information systems
- Issue:
- Volume 52(2015)
- Issue Display:
- Volume 52, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 52
- Issue:
- 2015
- Issue Sort Value:
- 2015-0052-2015-0000
- Page Start:
- 83
- Page End:
- 95
- Publication Date:
- 2015-08
- Subjects:
- Cloud computing -- Capacity planning -- Resource allocation
Database management -- Periodicals
Electronic data processing -- Periodicals
Bases de données -- Gestion -- Périodiques
Informatique -- Périodiques
Database management
Electronic data processing
Periodicals
005.7 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03064379 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.is.2015.03.003 ↗
- Languages:
- English
- ISSNs:
- 0306-4379
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4496.367300
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5681.xml