{"title":"支持nfp的Web服务组合的定量和定性方法","authors":"Hongbing Wang, Peisheng Ma, Xuan Zhou","doi":"10.1109/SCC.2012.16","DOIUrl":null,"url":null,"abstract":"Web service composition is a standard approach to create value-added services from existing ones. As the Web services on the Internet grows, there are more and more services providing identical functionalities while differing in their non-functional properties (NFPs). However, most of the existing techniques for NFP-aware service composition consider either only quantitative NFPs or only qualitative NFPs. In this paper, we present a service composition model considering both quantitative and qualitative NFPs. We propose two algorithms for conducting service composition. One combines global optimization with local selection into one mechanism. The other is a genetic algorithm based solution. We have conducted extensive experiments to evaluate the effectiveness of our proposals.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"A Quantitative and Qualitative Approach for NFP-Aware Web Service Composition\",\"authors\":\"Hongbing Wang, Peisheng Ma, Xuan Zhou\",\"doi\":\"10.1109/SCC.2012.16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Web service composition is a standard approach to create value-added services from existing ones. As the Web services on the Internet grows, there are more and more services providing identical functionalities while differing in their non-functional properties (NFPs). However, most of the existing techniques for NFP-aware service composition consider either only quantitative NFPs or only qualitative NFPs. In this paper, we present a service composition model considering both quantitative and qualitative NFPs. We propose two algorithms for conducting service composition. One combines global optimization with local selection into one mechanism. The other is a genetic algorithm based solution. We have conducted extensive experiments to evaluate the effectiveness of our proposals.\",\"PeriodicalId\":178841,\"journal\":{\"name\":\"2012 IEEE Ninth International Conference on Services Computing\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Ninth International Conference on Services Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCC.2012.16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Ninth International Conference on Services Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCC.2012.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Quantitative and Qualitative Approach for NFP-Aware Web Service Composition
Web service composition is a standard approach to create value-added services from existing ones. As the Web services on the Internet grows, there are more and more services providing identical functionalities while differing in their non-functional properties (NFPs). However, most of the existing techniques for NFP-aware service composition consider either only quantitative NFPs or only qualitative NFPs. In this paper, we present a service composition model considering both quantitative and qualitative NFPs. We propose two algorithms for conducting service composition. One combines global optimization with local selection into one mechanism. The other is a genetic algorithm based solution. We have conducted extensive experiments to evaluate the effectiveness of our proposals.