Personal Ontology for Service Composition Selection

碩士 === 國立中正大學 === 電機工程研究所 === 100 === In recent years, the web service research has developed rapidly. W3C and OASIS proposed a service oriented architecture standard in order to allow businesses and organizations to cooperate through the internet. In this standard architecture, web service...

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Bibliographic Details
Main Authors: Hung, JunYu, 洪潤宇
Other Authors: Alan Liu
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/27062278663977797858
Description
Summary:碩士 === 國立中正大學 === 電機工程研究所 === 100 === In recent years, the web service research has developed rapidly. W3C and OASIS proposed a service oriented architecture standard in order to allow businesses and organizations to cooperate through the internet. In this standard architecture, web service has the characteristics of cross-platform and reusable, it lets companies integrate different service providers when they build systems. It has become a mature and promising technology. With more complex functional requirements, relying on a single web service to achieve their goals is not easy, so the common solution today is composited web services to achieve user’s goal. With the rapid increase in the number of web services, selecting a suitable service composition from a variety of service compositions is a challenging topic. To solve the problem of how to select the correct web service components efficiently and quickly, quality of service (QoS) has become important indicator. In this thesis, we rely on workflow analysis to understand the functional requirements of each sub-process description and use this information for service discovery. In order to select web services with better quality quickly, we design a consistency formula before selecting service compositions. It could be seen as a threshold to choose a single service, not only ensuring the quality of service, but also reducing the time on composite services. Finally we use the quality requirements description to evaluate each candidate web service and get the most suitable composition according to user preference task processes and personal ontology.