The industry track of SIMUTools 2010.

Research Article

Simulation model driven performance evaluation for enterprise applications

  • @INPROCEEDINGS{10.4108/ICST.SIMUTOOLS2010.8706,
        author={Ernest  Sithole and Sally  McClean and Bryan  Scotney and Gerard  Parr and Adrian  Moore and Stephen  Dawson},
        title={Simulation model driven performance evaluation for enterprise applications},
        proceedings={The industry track of SIMUTools 2010.},
        publisher={ACM},
        proceedings_a={SIMULATIONWORKS},
        year={2010},
        month={5},
        keywords={Benchmarks Enterprise Applications Performance Evaluations},
        doi={10.4108/ICST.SIMUTOOLS2010.8706}
    }
    
  • Ernest Sithole
    Sally McClean
    Bryan Scotney
    Gerard Parr
    Adrian Moore
    Stephen Dawson
    Year: 2010
    Simulation model driven performance evaluation for enterprise applications
    SIMULATIONWORKS
    ICST
    DOI: 10.4108/ICST.SIMUTOOLS2010.8706
Ernest Sithole1,*, Sally McClean1,*, Bryan Scotney1,*, Gerard Parr1,*, Adrian Moore1,*, Stephen Dawson2,*
  • 1: School of Computing and Information Engineering, University of Ulster, Coleraine - BT52 1SA, Co. Londonderry, UK.
  • 2: SAP Research Belfast, Queens Island, Titanic Quarter, Belfast - BT3 9DT
*Contact email: e.sithole@ulster.ac.uk, si.mcclean@ulster.ac.uk, bw.scotney@ulster.ac.uk, gp.parr@ulster.ac.uk, aa.moore@ulster.ac.uk, stephen.dawson@sap.com

Abstract

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.