DocumentCode
2194900
Title
Unifying Cloud Management: Towards Overall Governance of Business Level Objectives
Author
Sedaghat, Mina ; Hernandez, F. ; Elmroth, Erik
Author_Institution
Dept. of Comput. Sci., Umea Univ., Umea, Sweden
fYear
2011
fDate
23-26 May 2011
Firstpage
591
Lastpage
597
Abstract
We address the challenge of providing unified cloud resource management towards an overall business level objective, given the multitude of managerial tasks to be performed and the complexity of any architecture to support them. Resource level management tasks include elasticity control, virtual machine and data placement, autonomous fault management, etc, which are intrinsically difficult problems since services normally have unknown lifetime and capacity demands that varies largely over time. To unify the management of these problems, (for optimization with respect to some higher level business level objective, like optimizing revenue while breaking no more than a certain percentage of service level agreements)becomes even more challenging as the resource level managerial challenges are far from independent. After providing the general problem formulation, we review recent approaches taken by the research community, including mainly general autonomic computing technology for large-scale environments and resource level management tools equipped with some business oriented or otherwise qualitative features. We propose and illustrate a policy-driven approach where a high-level management system monitors overall system and services behavior and adjusts lower level policies (e.g., thresholds for admission control, elasticity control, server consolidation level, etc) for optimization towards the measurable business level objectives.
Keywords
business data processing; cloud computing; fault tolerant computing; optimisation; resource allocation; virtual machines; architecture complexity; autonomic computing technology; autonomous fault management; business level objective; data placement; elasticity control; high-level management system; large-scale environment; managerial tasks; optimization; qualitative feature; research community; resource level management tasks; resource level management tools; services behavior; unified cloud resource management; virtual machine; Adaptation models; Elasticity; Engines; Monitoring; Optimization; Resource management; Autonomic Computing; Cloud governance; Policy-driven Management;
fLanguage
English
Publisher
ieee
Conference_Titel
Cluster, Cloud and Grid Computing (CCGrid), 2011 11th IEEE/ACM International Symposium on
Conference_Location
Newport Beach, CA
Print_ISBN
978-1-4577-0129-0
Electronic_ISBN
978-0-7695-4395-6
Type
conf
DOI
10.1109/CCGrid.2011.65
Filename
5948652
Link To Document