Software contention aware queueing network model of three-tier web systems (Work-In-Progress)

Shadi Ghaith, Miao Wang, Philip Perry, Liam Murphy

Research output: Contribution to conferencePaperpeer-review

6 Citations (Scopus)

Abstract

Using modelling to predict the performance characteristics of software applications typically uses Queueing Network Models representing the various system hardware resources. Leaving out the software resources, such as the limited number of threads, in such models leads to a reduced prediction accuracy. Accounting for Software Contention is a challenging task as existing techniques to model software components are complex and require deep knowledge of the software architecture. Furthermore, they also require complex measurement processes to obtain the model's service demands. In addition, solving the resultant model usually require simulation solvers which are often time consuming. In this work, we aim to provide a simpler model for three-tier web software systems which accounts for Software Contention that can be solved by time efficient analytical solvers. We achieve this by expanding the existing "Two-Level Iterative Queuing Modelling of Software Contention" method to handle the number of threads at the Application Server tier and the number of Data Sources at the Database Server tier. This is done in a generic manner to allow for extending the solution to other software components like memory and critical sections. Initial results show that our technique clearly outperforms existing techniques. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

Original languageEnglish
Pages273-276
Number of pages4
DOIs
Publication statusPublished (in print/issue) - 1 Jan 2014
Event5th ACM/SPEC International Conference on Performance Engineering, ICPE 2014 - Dublin, Ireland
Duration: 22 Mar 201426 Mar 2014

Conference

Conference5th ACM/SPEC International Conference on Performance Engineering, ICPE 2014
Country/TerritoryIreland
CityDublin
Period22/03/1426/03/14

Keywords

  • Performance models
  • Performance prediction
  • Software contention
  • Web applications

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