{"title":"E-Service Emergence: A Bio-Inspired Method of Composition","authors":"Hongbin Sun, Yongsheng Ding","doi":"10.1109/CISIS.2007.20","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce an emergence modeling approach to the study of e-service composition, which is inspired by the characteristics of emergence and self-evolution in biological neuroendocrine and immune system. E-services are represented by autonomous bio-entities (mobile agents with biological operation), each bio-entity is described by a Melay state machine. The request of integrating complex processes is translated to an automata analysis problem. Bio-entities establish emergent network based on the matching message to provide e-service composition. Affinity is a parameter which can measure the message matching ability of the bio-entity integrally, it depends on three factors, namely, the matching strength of message, the e-service quality score, and the trust. In this way, the method completes a series of work from composition to management autonomously. The simulation results show that the approach can significantly improve the e-service composition performance. It adapts well to the changes of dynamic environments","PeriodicalId":328547,"journal":{"name":"First International Conference on Complex, Intelligent and Software Intensive Systems (CISIS'07)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"First International Conference on Complex, Intelligent and Software Intensive Systems (CISIS'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISIS.2007.20","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
In this paper, we introduce an emergence modeling approach to the study of e-service composition, which is inspired by the characteristics of emergence and self-evolution in biological neuroendocrine and immune system. E-services are represented by autonomous bio-entities (mobile agents with biological operation), each bio-entity is described by a Melay state machine. The request of integrating complex processes is translated to an automata analysis problem. Bio-entities establish emergent network based on the matching message to provide e-service composition. Affinity is a parameter which can measure the message matching ability of the bio-entity integrally, it depends on three factors, namely, the matching strength of message, the e-service quality score, and the trust. In this way, the method completes a series of work from composition to management autonomously. The simulation results show that the approach can significantly improve the e-service composition performance. It adapts well to the changes of dynamic environments