Researches on manufacturing cloud service composition & optimization approach supporting for service statistic correlation

Author

Hui-fang Li ; Rui Jiang ; Si-yuan Ge

Author_Institution

Autom. Sch., Beijing Inst. of Technol., Beijing, China

fYear

2014

fDate

May 31 2014-June 2 2014

Firstpage

4149

Lastpage

4154

Abstract

In order to improve the quality of manufacturing cloud service composition, the influence of service statistic correlation on the QoS of cloud service composition was studied, then a cloud service composition & optimization approach supporting for service statistic correlation was proposed in this paper. Firstly, the statistic correlation between cloud services and their influence on QoS was analyzed, and then a cloud service statistic correlation model was built. Secondly, by introducing the index of statistic correlation degree into the QoS model of cloud service composition, the cloud service composition & optimization problem was solved by Particle Swarm Optimization (PSO) algorithm. Case study and analysis demonstrate that the proposed method is not only feasible and effectual, but also significant for promoting the development and application of cloud manufacturing.

Keywords

cloud computing; manufacturing systems; particle swarm optimisation; production engineering computing; statistical analysis; PSO algorithm; QoS model; cloud manufacturing; cloud service composition quality; cloud service statistic correlation model; optimization approach; particle swarm optimization; statistic correlation degree; Business; Communities; Correlation; Indexes; Manufacturing; Optimization; Quality of service; Cloud Manufacturing; Manufacturing Cloud Service; Quality of Service; Service Composition; Service Statistic Correlation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (2014 CCDC), The 26th Chinese

Conference_Location

Changsha

Print_ISBN

978-1-4799-3707-3

Type

conf

DOI

10.1109/CCDC.2014.6852908

Filename

6852908