Concurrency: state models & Java programs
Concurrency: state models & Java programs
Analysing software requirements specifications for performance
WOSP '02 Proceedings of the 3rd international workshop on Software and performance
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
Performance by Design: Computer Capacity Planning By Example
Performance by Design: Computer Capacity Planning By Example
Performance Engineering with the UML Profile for Schedulability, Performance and Time: A Case Study
MASCOTS '04 Proceedings of the The IEEE Computer Society's 12th Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
Towards Autonomic Distribution of Existing Object Oriented Programs
ICAS '06 Proceedings of the International Conference on Autonomic and Autonomous Systems
An Automatic Framework for Efficient Software Performance Evaluation and Optimization
ANSS '07 Proceedings of the 40th Annual Simulation Symposium
The Future of Software Performance Engineering
FOSE '07 2007 Future of Software Engineering
Rule-based automatic software performance diagnosis and improvement
WOSP '08 Proceedings of the 7th international workshop on Software and performance
A Model Transformation from the Palladio Component Model to Layered Queueing Networks
SIPEW '08 Proceedings of the SPEC international workshop on Performance Evaluation: Metrics, Models and Benchmarks
Automated Deployment of Distributed Software Components with Fault Tolerance Guarantees
SERA '08 Proceedings of the 2008 Sixth International Conference on Software Engineering Research, Management and Applications
The Palladio component model for model-driven performance prediction
Journal of Systems and Software
ArcheOpterix: An extendable tool for architecture optimization of AADL models
MOMPES '09 Proceedings of the 2009 ICSE Workshop on Model-Based Methodologies for Pervasive and Embedded Software
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
PerOpteryx: automated application of tactics in multi-objective software architecture optimization
Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS
Focussing multi-objective software architecture optimization using quality of service bounds
MODELS'10 Proceedings of the 2010 international conference on Models in software engineering
The application of FSP models in automatic optimization of software deployment
ASMTA'11 Proceedings of the 18th international conference on Analytical and stochastic modeling techniques and applications
An Extensible Framework for Improving a Distributed Software System's Deployment Architecture
IEEE Transactions on Software Engineering
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The quantitative performance evaluation of different deployments of distributed software objects over computational nodes is one of the main activities during the early stages of the design phase and should be supported by automated tools. The important design decision is to finding the optimal placement of objects, from the performance viewpoint, for different input workloads. Each deployment of objects may impose two kinds of delay on the overall performance of the software: first, the communicational delay due to the remote invocations among distributed objects and second, the computational delay due to the resource sharing by two or more concurrently executing object invocations. The object deployment problem can be formulated as an optimization problem to find the optimal deployment for which the total delay is minimal. In this paper an analytical model for delay prediction of object deployments considering the input workload of the software is presented. This model applies the object-oriented load metrics such as object population and object utilization to estimate the total amount of delay corresponding to a given object deployment. To achieve this, a novel method, called delay propagation, is proposed to compute the amount of delay corresponding to each method invocation which affects the overall response time of the software.In order to verify the proposed analytical delay predictor model, a statistical regression-based method is used. Moreover, by comparing the proposed method with the existing deployment optimization methods, which apply the Layered Queueing Networks to evaluate the performance of each deployment in the search space, a significant improvement in efficiency is observed due to the fast evaluation of each deployment instance in the search space.