ACM Transactions on Computer Systems (TOCS)
Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Automatic derivation of software performance models from CASE documents
Performance Evaluation
Optimal Resource-Aware Deployment Planning for Component-Based Distributed Applications
HPDC '04 Proceedings of the 13th IEEE International Symposium on High Performance Distributed Computing
Performance by unified model analysis (PUMA)
Proceedings of the 5th international workshop on Software and performance
Performance evaluation of UML software architectures with multiclass Queueing Network models
Proceedings of the 5th international workshop on Software and performance
Dynamic microcell assignment for massively multiplayer online gaming
NetGames '05 Proceedings of 4th ACM SIGCOMM workshop on Network and system support for games
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In order to ensure system performance, it is necessary to model the performance of a system during the entire development phase. Traditional performance modeling approaches, however, lack the ability to optimize the deployment of a distributed system, which is a critical performance aspect. Existing methodologies for performance optimization, on the other hand, often lack accuracy or the ability to express resource constraints. In this paper, an ILP-based methodology is presented that allows to optimize the deployment of a distributed system, starting from the UML system model. The applicability of the approach is demonstrated using two different case studies, and the approach is validated by comparing the calculated optimal deployment to the results of modeling the system performance using layered queuing networks.