Taguchi approach for performance evaluation of service-oriented software systems.

Service-oriented software systems are becoming increasingly common in the world today as big companies such as Microsoft and IBM advocate approaches focusing on assembly of system from distributed services. Although performance of such systems is a big problem, there is surprisingly an obvious lack of attention for evaluating the performance of enterprise-scale, service-oriented software systems. This thesis investigates the application of statistical tools in performance engineering domain for total quality management. In particular, the Taguchi approach is used as an efficient and systematic way to optimize designs for performance, quality, and cost. The aim is to improve the performance of software systems and to reduce application development cost by assembling services from known vendors or intranet services. The focus of this thesis is on the response time of service-oriented systems. Nevertheless, the developed methodology also applies to other performance issues, such as memory management and caching. The interaction problems of those issues are preserved for future work.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .L585. Source: Masters Abstracts International, Volume: 43-01, page: 0240. Adviser: Xiaobu Yuan. Thesis (M.Sc.)--University of Windsor (Canada), 2004

Combining Stochastic Process Algebras and Queueing Networks for Software Architecture Analysis

We propose an integrated approach to the functional and performance analysis of Software Architectures (SAs) based on Stochastic Process Algebras (SPAs) and Queueing Networks (QNs), in order to combine their main advantages: formal techniques for the verification of functional properties of systems for SPAs, and efficient performance analysis for QNs. We first introduce AEmilia, a SPA based architectural description language for the compositional, graphical and hierarchical modeling of SAs, which is equipped with suitable checks for the detection of architectural mismatches. Then we present a systematic approach to derive QN models from AEmilia specifications. This is based on the identification of three different classes of QN basic elements -- arrival processes, buffers, and service processes -- and on syntactic restrictions to be imposed to AEmilia specifications, so that each architectural component directly falls into one of the three classes. Although performance analysis could be carried out directly on the Markov chain (MC) underlying an AEmilia specification, having a QN model allows performance indices to be evaluated possibly by exact product form solutions or by well known approximate methods. Furthermore, unlike the underlying MC, the high level of abstraction of the QN model should ease the interpretation of the performance results at the architectural description level

Combining Stochastic Process Algebras and Queueing Networks for Software Architecture Analysis

We propose an integrated approach to the functional and performance analysis of Software Architectures (SAs) based on Stochastic Process Algebras (SPAs) and Queueing Networks (QNs), in order to combine their main advantages: formal techniques for the verification of functional properties of systems for SPAs, and efficient performance analysis for QNs. We first introduce Æmilia, a SPA based architectural description language for the compositional, graphical and hierarchical modeling of SAs, which is equipped with suitable checks for the detection of architectural mismatches. Then we present a systematic approach to derive QN models from Æmilia specifications. This is based on the identification of three different classes of QN basic elements --- arrival processes, buffers, and service processes --- and on syntactic restrictions to be imposed to Æmilia specifications, so that each architectural component directly falls into one of the three classes. Although performance analysis could be carried out directly on the Markov chain (MC) underlying an Æmilia specification, having a QN model allows performance indices to be evaluated possibly by exact product form solutions or by well known approximate methods. Furthermore, unlike the underlying MC, the high level of abstraction of the QN model should ease the interpretation of the performance results at the architectural description level

Combining Stochastic Process Algebras and Queueing Networks for Software Architecture Analysis

We propose an integrated approach to the functional and performance analysis of Software Architectures (SAs) based on Stochastic Process Algebras (SPAs) and Queueing Networks (QNs), in order to combine their main advantages: formal techniques for the verification of functional properties of systems for SPAs, and efficient performance analysis for QNs. We first introduce AEmilia, a SPA based architectural description language for the compositional, graphical and hierarchical modeling of SAs, which is equipped with suitable checks for the detection of architectural mismatches. Then we present a systematic approach to derive QN models from AEmilia specifications. This is based on the identification of three different classes of QN basic elements -- arrival processes, buffers, and service processes -- and on syntactic restrictions to be imposed to AEmilia specifications, so that each architectural component directly falls into one of the three classes. Although performance analysis could be carried out directly on the Markov chain (MC) underlying an AEmilia specification, having a QN model allows performance indices to be evaluated possibly by exact product form solutions or by well known approximate methods. Furthermore, unlike the underlying MC, the high level of abstraction of the QN model should ease the interpretation of the performance results at the architectural description level