Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
Performance-related completions for software specifications
Proceedings of the 24th International Conference on Software Engineering
Performance by Design: Computer Capacity Planning By Example
Performance by Design: Computer Capacity Planning By Example
The Palladio component model for model-driven performance prediction
Journal of Systems and Software
Automated Feature Model-Based Generation of Refinement Transformations
SEAA '09 Proceedings of the 2009 35th Euromicro Conference on Software Engineering and Advanced Applications
Modeling virtualized applications using machine learning techniques
VEE '12 Proceedings of the 8th ACM SIGPLAN/SIGOPS conference on Virtual Execution Environments
Trends in Computation, Communication and Storage and the Consequences for Data-intensive Science
HPCC '12 Proceedings of the 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems
Experimental evaluation of the performance-influencing factors of virtualized storage systems
EPEW'12 Proceedings of the 9th European conference on Computer Performance Engineering
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
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Virtualized environments introduce an additional abstraction layer on top of physical resources to enable the collective resource usage by multiple systems. With the rise of I/O-intensive applications, however, the virtualized storage of such shared environments can quickly become a bottleneck and lead to performance and scalability issues. The latter can be avoided through careful design of the application architecture and systematic capacity planning throughout the system life cycle. In current practice, however, virtualized storage and its performance-influencing design decisions are often neglected or treated as a black-box. In this work-in-progress paper, we propose a generic approach for performance modeling and prediction of virtualized storage systems at the software architecture level. More specifically, we propose two performance modeling approaches of virtualized systems. Furthermore, we propose two approaches how the performance models can be combined with architecture-level performance models. The goal is to cope with the increasing complexity of virtualized storage systems with the benefit of intuitive software architecture-level models.