Chaocan Xiang, Wendong Zhao, Chang Tian, Jingnan Nie, Jin Zhang
{"title":"QoS-aware, Optimal and Automated Service Composition with Users' Constraints","authors":"Chaocan Xiang, Wendong Zhao, Chang Tian, Jingnan Nie, Jin Zhang","doi":"10.1109/ICEBE.2011.59","DOIUrl":null,"url":null,"abstract":"In order to address a fundamental issue of automated service composition, this paper presents a novel approach for QoS-aware, optimal and automated service composition with users' constraints. Firstly, we construct the workflow of service composition automatically, according to users' service request. And then, we propose an Enhanced Genetic Algorithm to select the QoS-aware, optimal service composition, considering not only the QoS constraints but also the composing consumption constraints for the first time. With our approach, the result of service composition can meet different users' needs in various scenarios. The experiments validate correctness, significance and scalability of the approach.","PeriodicalId":231641,"journal":{"name":"2011 IEEE 8th International Conference on e-Business Engineering","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 8th International Conference on e-Business Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEBE.2011.59","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In order to address a fundamental issue of automated service composition, this paper presents a novel approach for QoS-aware, optimal and automated service composition with users' constraints. Firstly, we construct the workflow of service composition automatically, according to users' service request. And then, we propose an Enhanced Genetic Algorithm to select the QoS-aware, optimal service composition, considering not only the QoS constraints but also the composing consumption constraints for the first time. With our approach, the result of service composition can meet different users' needs in various scenarios. The experiments validate correctness, significance and scalability of the approach.