Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Deriving a queueing network based performance model from UML diagrams
Proceedings of the 2nd international workshop on Software and performance
Automatic derivation of software performance models from CASE documents
Performance Evaluation
From UML sequence diagrams and statecharts to analysable petri net models
WOSP '02 Proceedings of the 3rd international workshop on Software and performance
An analytical model for multi-tier internet services and its applications
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A method for evaluating the impact of software configuration parameters on e-commerce sites
Proceedings of the 5th international workshop on Software and performance
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
Performance modelling of distributed e-business applications using Queuing Petri Nets
ISPASS '03 Proceedings of the 2003 IEEE International Symposium on Performance Analysis of Systems and Software
Architecture-based reliability analysis of web services in multilayer environment
Proceedings of the 3rd International Workshop on Principles of Engineering Service-Oriented Systems
Autonomic load-testing framework
Proceedings of the 8th ACM international conference on Autonomic computing
Mitigating DoS Attacks Using Performance Model-Driven Adaptive Algorithms
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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The performance of a web application is affected by several factors. In this paper, the effects of two configurable software settings of J2EE application servers are discussed: the maximum size of the thread pool and the maximum size of the connection queue. Previous work has shown that both tuning parameters have a considerable impact on the performance metrics, and both of them should be taken into account when constructing a performance model of a web application. This paper presents a queueing network-based performance model that is able to capture the effect of the connection queue limit. New performance measurements which can help improving this model are also presented.