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

Hui Fang Li, Rui Jiang, Si Yuan Ge

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Citations (Scopus)

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.

Original languageEnglish
Title of host publication26th Chinese Control and Decision Conference, CCDC 2014
PublisherIEEE Computer Society
Pages4149-4154
Number of pages6
ISBN (Print)9781479937066
DOIs
Publication statusPublished - 2014
Event26th Chinese Control and Decision Conference, CCDC 2014 - Changsha, China
Duration: 31 May 20142 Jun 2014

Publication series

Name26th Chinese Control and Decision Conference, CCDC 2014

Conference

Conference26th Chinese Control and Decision Conference, CCDC 2014
Country/TerritoryChina
CityChangsha
Period31/05/142/06/14

Keywords

  • Cloud Manufacturing
  • Manufacturing Cloud Service
  • Quality of Service
  • Service Composition
  • Service Statistic Correlation

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