TY - GEN
T1 - Model-based planning for state-related changes to Infrastructure and Software as a Service instances in large data centers
AU - Hagen, Sebastian
AU - Kemper, Alfons
PY - 2010
Y1 - 2010
N2 - To deliver 3-tier applications as a Service in the Cloud state-related constraints crossing Infrastructure- and Software as a Service boundaries need to be managed. By automating the lifecycle of applications like databases, load balancers, and web application servers rich SaaS business services can be provided in the Cloud. We propose an object oriented planning approach based on state constraints to plan for changes of SaaS and IaaS components in the Cloud. We evaluate techniques for fast storing and restoring of large object oriented Configuration Management Databases and show that enforcing constraints in a procedural instead of a declarative way offers huge performance improvements. The advantages of our approach lie within the tight integration of the planning algorithm with object oriented models frequently used for Configuration Management Databases. In addition to that, the algorithm scales to a large number of nodes and preserves its runtime even for large, heavily loaded data centers.
AB - To deliver 3-tier applications as a Service in the Cloud state-related constraints crossing Infrastructure- and Software as a Service boundaries need to be managed. By automating the lifecycle of applications like databases, load balancers, and web application servers rich SaaS business services can be provided in the Cloud. We propose an object oriented planning approach based on state constraints to plan for changes of SaaS and IaaS components in the Cloud. We evaluate techniques for fast storing and restoring of large object oriented Configuration Management Databases and show that enforcing constraints in a procedural instead of a declarative way offers huge performance improvements. The advantages of our approach lie within the tight integration of the planning algorithm with object oriented models frequently used for Configuration Management Databases. In addition to that, the algorithm scales to a large number of nodes and preserves its runtime even for large, heavily loaded data centers.
KW - AI planning
KW - Application management
KW - IT change planning
KW - Service management
KW - State-based constraints
UR - http://www.scopus.com/inward/record.url?scp=77957939166&partnerID=8YFLogxK
U2 - 10.1109/CLOUD.2010.14
DO - 10.1109/CLOUD.2010.14
M3 - Conference contribution
AN - SCOPUS:77957939166
SN - 9780769541303
T3 - Proceedings - 2010 IEEE 3rd International Conference on Cloud Computing, CLOUD 2010
SP - 11
EP - 18
BT - Proceedings - 2010 IEEE 3rd International Conference on Cloud Computing, CLOUD 2010
T2 - 3rd IEEE International Conference on Cloud Computing, CLOUD 2010
Y2 - 5 July 2010 through 10 July 2010
ER -