Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Computing | en_US |
| dc.creator | He, Jianwen | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/7545 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | QoS-based web service optimization in cloud computing environment | en_US |
| dcterms.abstract | Thanks to the emergence and widespread of Service-oriented Architecture(SOA),Web service technology has got its attention around the Internet Community. However, single simple web service face the challenge of being unable to satisfy users' complex requirements in runtime environment as the amounts of web services become larger and larger. Therefore a lot of optimization solution has been proposed aimed to address the web service composition issue. Whereas most of them are of low efficiency and can not handle large-scale level web service. The dissertation has introduced a new kind of colony intelligent algorithm to address the web service composition, which is called Wolf Colony Algorithm. Furthermore, A distributed version of WCA in cloud computing environment has been proposed to handle large-scale web service composition problem. The experimental results show that the WCA outperforms in contrast to traditional heuristic algorithm such as particle swarm algorithm and genetic algorithm. And by implementing the WCA in hadoop framework, the efficiency has been improved greatly. | en_US |
| dcterms.extent | vii, 73 leaves : illustrations ; 30 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2014 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Web services. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b27577284.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.5 MB | Adobe PDF | View/Open |
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