A Clustering Approximation Technique for Queueing Network Models with a Large Number of Chains
IEEE Transactions on Computers
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
Designing Process Replication and Activation: A Quantitative Approach
IEEE Transactions on Software Engineering
Solution properties and convergence of an approximate mean value analysis algorithm
ACM SIGMETRICS Performance Evaluation Review
A Unifying Framework for the Approximate Solution of Closed Multiclass Queuing Networks
IEEE Transactions on Computers
IEEE Transactions on Software Engineering
Experiments with Improved Approximate Mean Value Analysis Algorithms
TOOLS '98 Proceedings of the 10th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
A Queue-Shift Approximation Technique for Product-Form Queueing
TOOLS '98 Proceedings of the 10th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
A performance engineering tool and method for distributing applications
CASCON '97 Proceedings of the 1997 conference of the Centre for Advanced Studies on Collaborative research
Migrating to web services: a performance engineering approach
Journal of Software Maintenance and Evolution: Research and Practice - Special issue: Web site evolution
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Linearizer is one of the best known approximation algorithms for obtaining numeric solutions for closed-product-form queueing networks. In the original exposition of Linearizer, the computational cost was stated to be O(MK/sup 3/) for a model with M queues and K job classes. It is shown that with some straightforward algebraic manipulation, Linearizer can be modified to require a cost that is only O(MK/sup 2/).