Paper Info
Title
Image selection as a service for cloud computing environments
Abstract
Customers of Cloud Services are expected to choose specific machine images to instantiate in order to host their workloads. Unfortunately very little information is provided to the users to enable them to make intelligent choices. We believe that as the number of images proliferates it will become increasingly difficult for users to decide effectively. Cloud service providers often allow their customers to instantiate standard system images, to modify their instances, and to store images of these customized instances for public or private future use. Storing modified instances as images enables customers to avoid re-provisioning and re-configuration of required resources thereby reducing their future costs. However Cloud service providers generally do not expose details regarding the configurations of the images in a rigorous canonical fashion nor offer services that assist clients in the best target image selection to support client transformation objectives. Rather, they allow customers to enter a free-form description of an image based on client's best effort. This means in order to find a “best fit” image to instantiate, a human user must review potentially thousands of image descriptions, reading each description to evaluate its suitability as a platform to host their source application. Furthermore, the actual content of the selected image may differ greatly from its description. Finally, even images that have been customized and retained for future use may need additional provisioning and customization to accommodate specific needs. In this paper we propose a service that accumulates image configuration details in a canonical fashion and a further service that employs an algorithm to order images per best fit /least cost in conformance to user-specified policies. These services collectively facilitate workload transformation into enterprise cloud environments.
Year
DOI
Venue
2010
10.1109/SOCA.2010.5707149
Service-Oriented Computing and Applications
Keywords
Field
DocType
business data processing,cloud computing,image processing,best fit image,client transformation,cloud computing environment,cloud service provider,enterprise cloud environment,image configuration,image description,image selection,machine image,system image,workload transformation,cloud computing,resource matching,workload migration
System image,Computer science,Workload,Server,Image processing,Provisioning,Software,Database,Distributed computing,Cloud computing,Personalization
Conference
ISBN
Citations 
PageRank 
978-1-4244-9802-4
11
0.59
References 
Authors
4
4
Name
Order
Citations
PageRank
Filepp, R.1110.59
Shwartz, L.2181.35
Christopher Ward324722.45
Kearney, R.D.4110.59