Energy-aware resource service scheduling based on utility evaluation in cloud manufacturing system

被引:98
作者
Cheng, Ying [1 ]
Tao, Fei [1 ]
Liu, Yilong [1 ]
Zhao, Dongming [2 ]
Zhang, Lin [1 ]
Xu, Lida [3 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[2] Univ Michigan, Sch Automat Sci & Elect Engn, Dearborn, MI 48128 USA
[3] Old Dominion Univ, Dept Informat Technol & Decis Sci, Norfolk, VA USA
关键词
Cloud manufacturing; resources service scheduling; utility evaluation; system-centered scheduling; energy aware; SUPPLY CHAIN; GRID SYSTEM; GENETIC ALGORITHM; WEB SERVICES; TRUST-QOS; ALLOCATION; ENTERPRISE; SELECTION; SUPPORT; MODEL;
D O I
10.1177/0954405413492966
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In order to realize the manufacturing resource sharing and optimal allocation, many advanced manufacturing modes and technologies have been proposed and researched, but few works have been emphasized on resource service and capability transaction and scheduling management. With these conditions, in this article, the concept of cloud manufacturing mode is first briefly introduced, and a general cloud manufacturing resource service scheduling model is established. Then, the comprehensive utility models, which consider energy consumption, cost, and risk for the three sides (i.e. provider, consumer, and operator), are established in the resource service scheduling process in cloud manufacturing system. Four kinds of resource service scheduling modes, which are provider centered, consumer centered, operator centered, and system centered, are studied. These modes are based on the utility models that are investigated, as well as the system-centered cooperative scheduling method that is designed with risk-sharing strategy. The experimental results show that the system-centered scheduling method has the highest potential for realizing the aim of cloud manufacturing, and the system-centered cooperative scheduling method is rational to obtain the higher maximal utilities of the whole system and the three key users at the same time. It promotes the higher efficiency and utility, a higher rate of sharing, green and on-demand use of decentralized manufacturing resources and capability services in cloud manufacturing systems.
引用
收藏
页码:1901 / 1915
页数:15
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