A scientific workflow management system architecture and its scheduling based on cloud service platform for manufacturing big data analytics

被引：63

作者：

Li, Xiu ^{[1
]}

Song, Jingdong ^{[1
]}

Huang, Biqing ^{[2
]}

机构：

[1] Tsinghua Univ, Grad Sch Shenzhen, Div Informat Sci & Technol, Shenzhen 518055, Peoples R China

[2] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2016年 / 84卷 / 1-4期

基金：

中国国家自然科学基金;

关键词：

Manufacturing big data; Scientific workflow; Scheduling algorithm; Cloud service platform; IMPLEMENTATION; PERFORMANCE;

D O I：

10.1007/s00170-015-7804-9

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

To improve the efficiency and productivity of modern manufacturing, the requirements for enterprises are discussed. The new emerged technologies such as cloud computing and internet of things are analyzed and the bottlenecks faced by enterprises in manufacturing big data analytics are investigated. Scientific workflow technology as a method to solve the problems is introduced and an architecture of scientific workflow management system based on cloud manufacturing service platform is proposed. The functions of each layer in the architecture are described in detail and implemented with an existing workflow system as a case study. The workflow scheduling algorithm is the key issue of management system, and the related work is reviewed. This paper takes the general problems of existing algorithms as the motivation to propose a novel scheduling algorithm called MP (max percentages) algorithm. The simulation results indicate that the proposed algorithm has performed better than the other five classic algorithms with respect to both the total completion time and load balancing level.

引用

页码：119 / 131

页数：13

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