Performance prediction of component- and pattern-based middleware for distributed systems
Proceedings of the 4th on Middleware doctoral symposium
Improving the performances of JMS-based applications
International Journal of Autonomic Computing
Performance evaluation of message-oriented middleware using the SPECjms2007 benchmark
Performance Evaluation
Modeling event-driven service-oriented systems using the palladio component model
Proceedings of the 1st international workshop on Quality of service-oriented software systems
Self-optimization of clustered message-oriented middleware
OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems: CoopIS, DOA, ODBASE, GADA, and IS - Volume Part I
Parametric performance completions for model-driven performance prediction
Performance Evaluation
Predictive modelling of peer-to-peer event-driven communication in component-based systems
EPEW'10 Proceedings of the 7th European performance engineering conference on Computer performance engineering
Integration of event-based communication in the palladio software quality prediction framework
Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS
Adapting distributed real-time and embedded pub/sub middleware for cloud computing environments
Proceedings of the ACM/IFIP/USENIX 11th International Conference on Middleware
Constructing performance model of JMS middleware platform
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
Performance modeling and analysis of message-oriented event-driven systems
Software and Systems Modeling (SoSyM)
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The Java messaging service (JMS) is a means to organize communication among distributed applications according to the publish/subscribe principle. If the subscribers install filter rules on the JMS server, JMS can be used as a message routing platform, but it is not clear whether its message throughput is sufficiently high to support large-scale systems. We perform measurements for the FioranoMQ JMS server and derive a simple model for its message processing time that takes message filters and the message replication grade into account. Then, we analyze the JMS server capacity and the message waiting time for various application scenarios. We show that the message waiting time is not an issue as long as the server throughput is sufficiently high. Finally, we assess the capacity of two different distributed JMS architectures whose objective is to increase the capacity of the JMS beyond the limit of a single server.