Characterizing Secure Dynamic Web Applications Scalability
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Experiences with Simulations - A Light and Fast Model for Secure Web Applications
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
Designing an overload control strategy for secure e-commerce applications
Computer Networks: The International Journal of Computer and Telecommunications Networking
Monitoring and analysing a Grid Middleware Node
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Automated extraction of palladio component models from running enterprise Java applications
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
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Future Generation Computer Systems
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ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
Automated extraction of architecture-level performance models of distributed component-based systems
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
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In this paper we present the eDragon environment, a research platform created to perform complete performance analysis of new Web-based technologies. eDragon enables the understanding of how application servers work in both sequential and parallel platforms offering a new insight in the usage of system resources. The environment is composed of a set of instrumentation modules, a performance analysis and visualization tool and a set of experimental methodologies to perform complete performance analysis of Web-based technologies. This paper describes the design and implementation of this research platform and highlights some of its main functionalities. We will also show how a detailed analytical view can be obtained through the application of a bottom-up strategy, starting with a group of system events and advancing to more complex performance metrics using a continuous derivation process.