Distributed component technologies and their software engineering implications
Proceedings of the 24th International Conference on Software Engineering
PASASM: a method for the performance assessment of software architectures
WOSP '02 Proceedings of the 3rd international workshop on Software and performance
The Future of Software Performance Engineering
FOSE '07 2007 Future of Software Engineering
Performance modeling for service oriented architectures
Companion of the 30th international conference on Software engineering
Service-Oriented Performance Modeling the MULE Enterprise Service Bus (ESB) Loan Broker Application
SEAA '09 Proceedings of the 2009 35th Euromicro Conference on Software Engineering and Advanced Applications
Dynamic service selection capability for load balancing in enterprise service bus
CEA'10 Proceedings of the 4th WSEAS international conference on Computer engineering and applications
Load-Balancing Dynamic Service Binding in Composition Execution Engines
APSCC '10 Proceedings of the 2010 IEEE Asia-Pacific Services Computing Conference
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
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In this paper we describe our preliminary experiences of a performance modeling "Blending" approach for early life-cycle architecture assessment and risk mitigation in a large enterprise integration project. The goal was to use performance modeling to assist with defining the requirements for the system and to identify areas of architecture and technology risk which could be addressed in future phases of the project. We modified our Service Oriented Performance Modeling approach to enable useful models to be constructed from a variety of imprecise and incomplete information sources prior to the existence of concrete requirements or implementations. Activities iterated over two phases and included scenario and workload modeling in phase 1, and integration infrastructure, workload and blended modeling in phase 2. The resulting models enabled early discovery and exploration of critical assumptions and architectural alternatives. One critical assumption is explored in more detail as an example. This is the impact of the specific location of services, which was predicted to require a large variation in resource requirements across the integration infrastructure. We demonstrate this with example models and explore possible solutions based on dynamic service load balancing.