Performance Measurement of Design Patterns for Service-Oriented Architecture

Service-Oriented Architecture (SOA) is a computing paradigm where large complex applications are composed of independent components offering services to one another through well-defined interfaces. SOA patterns provide generic solutions for different architectural, design and implementation problems of SOA applications. SOA patterns differ in scope and objectives, so their effect on system performance is also different, either positive or negative. SOA patterns introduce means of reliable messaging. Application of patterns facilitates workflow implementations ensuring business processes are completed once started despite system failures. Platform vendors provide native implementation to some patterns hidden from developers. Such enhancements to web service systems compromise system performance. This thesis aims to measures performance effects of applying different patterns at various levels, helping SOA designers to better understand performance impacts of their applications and provide knowledge to make trade-offs between performance and other software properties affected by patterns. A predictive evaluation approach will demonstrate estimating performance early in the lifecycle.