DocumentCode
2759415
Title
ReSF: Resource Selection Framework Based on P2P Network for Remanufacturing Production System
Author
Yang, Gao ; Hong-yu, Zhang ; Hua, Ma
Author_Institution
Bus. Sch., Central South Univ., Changsha, China
Volume
2
fYear
2009
fDate
25-26 July 2009
Firstpage
279
Lastpage
282
Abstract
Information sharing and coordination were an effective approach to reduce the uncertainties of remanufacturing production and improve the accuracy of production planning. Considering the characteristics of the remanufacturing production system, a resource selection framework named ReSF was proposed. It was built on a two-layer P2P information sharing model based on topic cluster, and could achieve a high performance of information query in the dynamic remanufacturing production environment. Encapsulated into web services, all the resource information was published in P2P network, and was described by OWL-S on the basis of semantic web services in ReSF. A computing method of the semantic similarity and an algorithm for web services matching based on it were designed to search the most appropriate one from candidate resources on the semantic level, which made it possible to acquire resource information timely and accurately and to meet maximum interests of the related parties in remanufacturing production. Finally, this framework was discussed and evaluated.
Keywords
peer-to-peer computing; production planning; recycling; OWLS; P2P network; information query; information sharing; production planning; remanufacturing production system; resource selection framework; semantic web services; Costs; Electronic mail; Information technology; Manufacturing systems; Network topology; Production planning; Production systems; Semantic Web; Uncertainty; Web services; P2P network; information sharing; remanufacturing; resource selection; semantic web services;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Computer Science, 2009. ITCS 2009. International Conference on
Conference_Location
Kiev
Print_ISBN
978-0-7695-3688-0
Type
conf
DOI
10.1109/ITCS.2009.193
Filename
5190234
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