DocumentCode :
629640
Title :
Towards predictive cost models for cloud ecosystems: Poster paper
Author :
Molka, Karsten ; Byrne, James
Author_Institution :
SAP Appl. Res., TI SAP Next Bus. & Technol., Belfast, UK
fYear :
2013
fDate :
29-31 May 2013
Firstpage :
1
Lastpage :
2
Abstract :
The rapid increase in the demand for cloud computing is driving a more recent increasing move towards multi-cloud environments by infrastructure providers. However, one of the main challenges for infrastructure providers is in sustaining profitability while provisioning services and components in such multi-cloud environments. This poster paper presents work towards predictive cost modeling for cloud ecosystems. Both real-time and historical analysis of service, virtual and physical resource information gathered from cloud infrastructure is used to drive both economic assessment and prediction models which can anticipate future service economic trends and the effect on total cost of ownership at the infrastructure provider side. This aids driving decisions to be made based on increased or reduced costs, which aids decision-support to effectively fulfil SLA requirements.
Keywords :
cloud computing; contracts; costing; profitability; SLA requirements; cloud computing; cloud ecosystems; component provisioning; economic assessment; historical analysis; infrastructure providers; multicloud environments; physical resource information; prediction models; predictive cost models; profitability; real-time analysis; service economic trends; service provisioning; total ownership cost effect; virtual resource information; Biological system modeling; Cloud computing; Computational modeling; Economics; Ecosystems; IP networks; Predictive models; cloud computing; cost modeling; cost prediction; economic modeling; hybrid clouds; multi clouds;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Research Challenges in Information Science (RCIS), 2013 IEEE Seventh International Conference on
Conference_Location :
Paris
ISSN :
2151-1349
Print_ISBN :
978-1-4673-2912-5
Type :
conf
DOI :
10.1109/RCIS.2013.6577736
Filename :
6577736
Link To Document :
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