{"title":"Performance Analysis of a Composition of Middleware Patterns (Short Paper)","authors":"Paul J. Vandal, S. Gokhale","doi":"10.1109/QSIC.2008.47","DOIUrl":null,"url":null,"abstract":"A key enabling technology for the SOA-based approach is middleware, which comprises of reusable building blocks codifying design patterns. In the SOA-based approach, a system is typically implemented using a composition of a group of such patterns, referred to as a vertical variation. The patterns used in a composition and their configuration options can have a a profound impact on system performance. In this paper we present a model-based performance analysis methodology for a system built using a composition of the reactor, active object and monitor object patterns. We implement the performance model using CSIM and illustrate the methodology using examples. By enabling design-time performance analysis, our methodology alleviates many of the disadvantages of post-implementation performance analysis approaches. The methodology can thus provide key guidance towards meeting the performance objectives of a system in a cost-effective manner.","PeriodicalId":6446,"journal":{"name":"2008 The Eighth International Conference on Quality Software","volume":"48 1","pages":"175-180"},"PeriodicalIF":0.0000,"publicationDate":"2008-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 The Eighth International Conference on Quality Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QSIC.2008.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A key enabling technology for the SOA-based approach is middleware, which comprises of reusable building blocks codifying design patterns. In the SOA-based approach, a system is typically implemented using a composition of a group of such patterns, referred to as a vertical variation. The patterns used in a composition and their configuration options can have a a profound impact on system performance. In this paper we present a model-based performance analysis methodology for a system built using a composition of the reactor, active object and monitor object patterns. We implement the performance model using CSIM and illustrate the methodology using examples. By enabling design-time performance analysis, our methodology alleviates many of the disadvantages of post-implementation performance analysis approaches. The methodology can thus provide key guidance towards meeting the performance objectives of a system in a cost-effective manner.