Asymptotic convergence of scheduling policies with respect to slowdown
Performance Evaluation
Optimal state-free, size-aware dispatching for heterogeneous M/G/-type systems
Performance Evaluation - Performance 2005
The processor-sharing queue with bulk arrivals and phase-type services
Performance Evaluation
Performance modelling and evaluation of computer systems
Journal of Computer and System Sciences - Special issue: Performance modelling and evaluation of computer systems
Neural network-based mean-variance-skewness model for portfolio selection
Computers and Operations Research
M/G/1 queue with deterministic reneging times
Performance Evaluation
MASCOTS '07 Proceedings of the 2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
SAP Performance Optimization Guide
SAP Performance Optimization Guide
Delay performance in stochastic processing networks with priority service
Operations Research Letters
Analysis of the M/G/1 processor-sharing queue with bulk arrivals
Operations Research Letters
A note on comparing response times in the M/GI/1/FB and M/GI/1/PS queues
Operations Research Letters
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Performance evaluations for enterprise applications running over IT systems are difficult to carry out given the multiplicity and variability of the operational components that constitute the dispersed IT infrastructures. To overcome this challenge, most of the approaches for performance assessment employ benchmarking strategies. While benchmarking methods provide exact indications on the performance capability of the measured facility, the results so obtained mostly apply to specific physical implementations considered in benchmark runs. The information provided by benchmark data thus restricts the ability to carry out meaningful performance analysis unless wide varieties of physical scenarios are generated for comparative studies. Given the logistical drawbacks associated with benchmarking techniques, we therefore propose a flexible model-based approach to determine quantitative performance for applications in IT systems by producing a range of performance models through the use of generic components that are easily assembled in simulation environments. Our approach initially considers a Tier 2 model framework whose components are derived from the SAP Sell-from-Stock application routine running on a multi-core processor server. The modelled framework is extensible enough to provide the definitions of resource consumptions patterns of different applications as well as the variety of server hardware systems. The simulations of our initial models developed so far generate results that are comparable to measurements obtained for scenarios in the low and moderate loading levels.