TY - GEN
T1 - Modeling of service correlation for service composition in cloud manufacturing
AU - Wang, Fei
AU - Laili, Yuanjun
AU - Zhang, Lin
AU - Xing, Chi
AU - Guo, Liqin
N1 - Publisher Copyright:
© 2019 Dime Universita di Genova, DIMEG University of Calabria.
PY - 2019
Y1 - 2019
N2 - Cloud manufacturing (CMfg), integrating distributed manufacturing resources as services to cloud center, aims at intelligent, green, and economic customized manufacturing. The optimal composition of services to fulfill particular manufacturing requirement is a core issue to realize efficient cloud manufacturing. Many researchers have studied the problem considering the Quality-of-Service (QoS) of independent services. However, the correlation between services is rarely considered. In this paper, the importance of service correlation is emphasized. Two kinds of service correlation, service exclusion and service collaboration, are modeled for service composition. An improved algorithm DET, which combines Differential Evolution Algorithm (DE) with a Tabu table based on service exclusive and collaborative relationships, is designed to filter composable services and find better solutions for complex tasks. Experiments have shown the effects of service correlation on the quality of composed services and demonstrated the effectiveness of the proposed method DET compared with traditional DE.
AB - Cloud manufacturing (CMfg), integrating distributed manufacturing resources as services to cloud center, aims at intelligent, green, and economic customized manufacturing. The optimal composition of services to fulfill particular manufacturing requirement is a core issue to realize efficient cloud manufacturing. Many researchers have studied the problem considering the Quality-of-Service (QoS) of independent services. However, the correlation between services is rarely considered. In this paper, the importance of service correlation is emphasized. Two kinds of service correlation, service exclusion and service collaboration, are modeled for service composition. An improved algorithm DET, which combines Differential Evolution Algorithm (DE) with a Tabu table based on service exclusive and collaborative relationships, is designed to filter composable services and find better solutions for complex tasks. Experiments have shown the effects of service correlation on the quality of composed services and demonstrated the effectiveness of the proposed method DET compared with traditional DE.
KW - Cloud manufacturing
KW - Differential evolution
KW - Service composition
KW - Service correlation
KW - Tabu table
UR - https://www.scopus.com/pages/publications/85073800855
M3 - 会议稿件
AN - SCOPUS:85073800855
T3 - 31st European Modeling and Simulation Symposium, EMSS 2019
SP - 59
EP - 65
BT - 31st European Modeling and Simulation Symposium, EMSS 2019
A2 - Affenzeller, Michael
A2 - Bruzzone, Agostino G.
A2 - Longo, Francesco
A2 - Pereira, Guilherme
PB - Dime University of Genoa
T2 - 31st European Modeling and Simulation Symposium, EMSS 2019
Y2 - 18 September 2019 through 20 September 2019
ER -