The document summarizes a paper on cost-optimal outsourcing of applications into cloud computing environments. It discusses three potential solutions: hosting the application entirely on-premises, splitting the application across different cloud providers' small instances, and splitting it across small and large instances from multiple providers. The paper contributions include a mathematical model for defining application templates, provisioning services, and plans to optimize costs. It also describes an algorithm to decompose deployment graphs and map them to a constraint optimization problem to find the optimal deployment plan. Future work areas discussed include data-centric and quality-aware service composition.

1. SOSOA – Group EPFL
Prof. Boi Faltings
Immanuel Trummer

2. Cost-Optimal Outsourcing of
Applications into the Clouds
I. Trummer, F. Leymann,
R. Mietzner, W. Binder
IEEE Conference on Cloud Computing
Technology and Science 2010

3. Basic Problem: How to Minimize the
Running Costs of an Application?
Server
App.
Server
DBMS
Web
Interface
DB
1st Solution: On-Premises
X $/Hour
Constraint:
T-SQL
Constraint:
Availability>99.9

4. Server
App.
Server
DBMS
Small
Instance
JBoss MySQL
Provider 1
Basic Problem: How to Minimize the
Running Costs of an Application?
Web
Interface
DBCustom
Standard
2nd Solution: Y $/Hour
Small
Instance
JBoss MySQL
Provider 1

5. Large
Instance
Provider 3
DB2
Large
Instance
WebSph.
Provider 2
DBMS
Large
Instance
DB2
Basic Problem: How to Minimize the
Running Costs of an Application?
Server
App.
Server
Web
Interface
DBCustom
Standard
3rd Solution: Z $/Hour
Small
Instance
JBoss MySQL
Provider 1
Large
Instance
WebSph.
Provider 2&3

6. Paper Contributions
• Mathematical model:
– Application Templates
– Provisioning Services
– Provisioning Plans
• Algorithm for finding the optimal plan
– Decomposition of deployment graphs
– Mapping between deployment graphs
– Transformation into Constraint Optimization Problem
• Corresponding Benchmarks

7. Future Work

8. (Geospatial-)Data Centric Service
Composition
• Z. Liu, A. Ranganathan, and A. Riabov:
“A planning approach for message-oriented semantic web service
composition”
in Proceedings of the National Conference on Artificial Intelligence,
2007
• J. Ambite and D. Kapoor:
“Automatically composing data workflows with relational
descriptions and shim services”
in The Semantic Web, 2007
• P. Yue, L. Di, W. Yang, G. Yu, and P. Zhao:
“Path planning for chaining geospatial web services”
in Web and Wireless Geographical Information Systems, 2006
• M. Lutz:
“Ontology-based descriptions for semantic discovery and
composition of geoprocessing services”
in Geoinformatica, 2007

9. Quality-Aware Service Composition
• L. Zeng, B. Benatallah, M. Dumas, J. Kalagnanam, and Q. Sheng:
“Quality driven web services composition”
in Proceedings of the 12th international conference on World Wide
Web, 2003
• G. Canfora, M. Di Penta, R. Esposito, and M. Villani:
“An approach for QoS-aware service composition based on
genetic algorithms”
in Conference on Genetic and evolutionary computation, 2005
• A. Ben Hassine, S. Matsubara, and T. Ishida:
“A constraint-based approach to horizontal web service
composition”
in The Semantic Web-ISWC 2006
• F. Rosenberg, P. Leitner, A. Michlmayr, P. Celikovic, and S. Dustdar:
”Towards composition as a service-a quality of service driven
approach”
in IEEE Conference on Data Engineering, 2009