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Cluster Computing
Published in: Cluster Computing 3/2019

29-12-2017

Research for service flow module granularity design based on fuzzy spaces quotient theory

Author: Fei Zhang

Published in: Cluster Computing | Special Issue 3/2019

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Abstract

In the research of modular design of service flow, this paper proposes a method to partition the service flow module based on fuzzy spaces quotient theory to reduce the subjectivity of module granularity selection. On the basis of service elements identification, the interrelation among service elements is analyzed in detail. And the further evaluation is made from three aspects such as service flow relevance, service source relevance and service function relevance. By working out similarity matrix between service elements and clustering attributes, the integrated fuzzy similarity matrix is obtained. And the service flow module granularity space is educated by cluster service elements through acquiring hierarchical structure using algorithm. Finally by the grey relational analysis theory and the proper index system, the optimal project of service flow module can be obtained. In this paper, the feasibility of the method above is verified by the maintenance service flow and the module granularity design of the excavator walking mechanism.
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Metadata
Title
Research for service flow module granularity design based on fuzzy spaces quotient theory
Author
Fei Zhang
Publication date
29-12-2017
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 3/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1623-8

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