Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
A Note on the Computational Cost of the Linearizer Algorithm for Queueing Networks
IEEE Transactions on Computers
OSF DCE: guide to developing distributed applications
OSF DCE: guide to developing distributed applications
IEEE Transactions on Computers
Asymptotic analysis of multiclass closed queueing networks: common bottleneck
Performance Evaluation
Client/server programming with Java and CORBA
Client/server programming with Java and CORBA
Asymptotic analysis of multiclass closed queueing networks: multiple bottlenecks
Performance Evaluation
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
Linearizer: a heuristic algorithm for queueing network models of computing systems
Communications of the ACM
IEEE Transactions on Software Engineering
Automatic Generation of a Software Performance Model Using an Object-Oriented Prototype
MASCOTS '95 Proceedings of the 3rd International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
Performance Engineering of Distributed Software Process Architectures
MMB '95 Proceedings of the 8th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation: Quantitative Evaluation of Computing and Communication Systems
Object Allocation for Distributed Applications with Complex Workloads
TOOLS '00 Proceedings of the 11th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
Migrating to Web Services " Latency and Scalability
WSE '02 Proceedings of the Fourth International Workshop on Web Site Evolution (WSE'02)
Migrating to web services: a performance engineering approach
Journal of Software Maintenance and Evolution: Research and Practice - Special issue: Web site evolution
A performance analysis method for autonomic computing systems
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
TEx-Sys model for building intelligent tutoring systems
Computers & Education
WSEAS Transactions on Computers
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Performance model driven QoS guarantees and optimization in clouds
CLOUD '09 Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing
BAP: a benchmark-driven algebraic method for the performance engineering of customized services
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
Information and Software Technology
Model-based performance testing (NIER track)
Proceedings of the 33rd International Conference on Software Engineering
Autonomic load-testing framework
Proceedings of the 8th ACM international conference on Autonomic computing
CloudOpt: multi-goal optimization of application deployments across a cloud
Proceedings of the 7th International Conference on Network and Services Management
Mitigating DoS Attacks Using Performance Model-Driven Adaptive Algorithms
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Efficient optimization of software performance models via parameter-space pruning
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
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Distributed application systems are composed of classes of objects with instances that interact to accomplish common goals. Such systems can have many classes of users with many types of requests. Furthermore, the relative load of these classes can shift throughout the day causing changes to system behavior and bottlenecks. When designing and deploying such systems it is necessary to determine a process replication and threading policy for the server processes that contain the objects, as well as process activation policies. To avoid bottlenecks the policy must support all possible workload conditions. Licensing, implementation, or resource constraints can limit the number of permitted replicas or threads of a server process. Process activation policies determine whether a server is persistent or should be created and terminated with each call. The purpose of this paper is to describe quantitative techniques for choosing process replication or threading levels and process activation policies. Inappropriate policies can lead to unnecessary queuing delays for callers or unnecessarily high consumption of memory resources. The algorithms presented consider all workload conditions, are iterative in nature, and are hybrid mathematical programming and analytic performance evaluation methods. An example is given to demonstrate the technique and describe how the results can be applied during software design and deployment.