Model-based runtime reconfiguration of component-based systems
Proceedings of the Warm Up Workshop for ACM/IEEE ICSE 2010
Workload-intensity-sensitive timing behavior analysis for distributed multi-user software systems
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
SyLaGen: an extendable tool environment for generating load
MMB&DFT'10 Proceedings of the 15th international GI/ITG conference on Measurement, Modelling, and Evaluation of Computing Systems and Dependability and Fault Tolerance
Self-protecting and self-optimizing database systems: implementation and experimental evaluation
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
Modeling variations in load intensity over time
Proceedings of the third international workshop on Large scale testing
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This paper presents an approach and a corresponding tool for generating probabilistic and intensity-varying workload for Web-based software systems. The workload to be generated is specified in two types of models. An application model specifies the possible interactions with the Web-based software system, as well as all required low-level protocol details by means of a hierarchical finite state machine. Based on the application model, the probabilistic usage is specified in corresponding user behavior models by means of Markov chains. Our tool Markov4JMeter implements our approach to probabilistic workload generation by extending the popular workload generation tool JMeter. A case study demonstrates how probabilistic workload for a sample Web application can be modeled and executed using Markov4JMeter.