Study on Hierarchical Service Composition in Cloud Manufacturing

China Mechanical Engineering ›› 2013, Vol. 24 ›› Issue (10): 1349-1356.

Previous Articles Next Articles

Study on Hierarchical Service Composition in Cloud Manufacturing

Liu Weining;Ma Gang;Liu Bo

Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education,Chongqing University,Chongqing,400044

Online:2013-05-25 Published:2013-05-28
Supported by:

National Natural Science Foundation of China（No. 61203135）;

The National Key Technology R&D Program（No. 2012BAH19F01）;
Fundamental Research Funds for the Central Universities( No. CDJZR12180013 )

基于层次化的云制造服务组合研究

刘卫宁;马刚;刘波

重庆大学信息物理社会可信服务计算教育部重点实验室,重庆,400044

基金资助:
国家自然科学基金资助项目(61203135);“十二五”国家科技支撑计划资助项目(2012BAH19F01);重庆市科委自然科学基金资助项目(CSCT2012JJA40020);中央高校基本科研业务费资助项目(CDJZR12180013)
National Natural Science Foundation of China（No. 61203135）;

The National Key Technology R&D Program（No. 2012BAH19F01）;
Fundamental Research Funds for the Central Universities( No. CDJZR12180013 )

Abstract

Abstract:

To cope with the quality of service(QoS) bottleneck and evaluation deviation of composite services path in cloud manufacturing(CMfg) system due to ignoring the hierarchical characteristics of the manufacturing processes,a mathematical model and a solution algorithm were proposed and studied.Initially,
the hierarchical manufacturing cloud services composition(H-MCSC) model was formulated based on the hierarchical manufacturing implementation processes.Then,a simulated annealing algorithm was developed based on the analysis and properties of the H-MCSC model.Within the algorithm,a pruning strategy based on sub-paths QoS constraints was designed to improve the efficiency of the algorithm.Simulation experimental results prove the validity of the model and algorithm.

Key words: cloud manufacturing, service composition, hierarchical, quality of service, simulated annealing algorithm

摘要：

针对云制造环境下,因忽略制造过程层次化特性导致组合服务路径存在服务质量瓶颈及整体服务质量计算偏差的问题,建立了新的问题模型并提出了求解算法。首先通过分析制造任务的层次化特性，构建了层次化的云制造服务组合模型。继而使用模拟退火算法求解该模型，为提高算法的效率利用子路径的服务质量约束设计了提前剪枝策略。仿真实验证明了模型的正确性和算法的有效性。

关键词: 云制造, 服务组合, 层次化, 服务质量, 模拟退火算法

CLC Number:

TP391

LIU Wei-Ning, MA Gang, LIU Bei. Study on Hierarchical Service Composition in Cloud Manufacturing[J]. China Mechanical Engineering, 2013, 24(10): 1349-1356.

刘卫宁, 马刚, 刘波. 基于层次化的云制造服务组合研究[J]. 中国机械工程, 2013, 24(10): 1349-1356.

References

[1]Tao Fei, Zhao Dongming, Hu Yefa, et al.ResourceService Composition and Its Optimal SelectionBased on Particles Warm Optimization in Manufac-turing Grid System [J].IEEE Transactions on In-dustrial Informatics,2008,4(4):315-327.
[2]Zhang L,Guo H,Tao F,et al.Flexible Managementof Resource Service Composition in Cloud Manufac-turing[C]//2010 IEEE International Conference onIndustrial Engineering Engineering Management(IE&EM 2010).Macao,2010:2278-2282.
[3]李伯虎[1,2],张霖[1],王时龙[3],陶飞[1],曹军威[4],姜晓丹[5],宋晓[1],柴旭东[2].云制造——面向服务的网络化制造新模式[J].计算机集成制造系统,2010,16(1):1-7. 28
[4]侯伟伟[1],刘检华[1],宁汝新[1],尚炜[1].基于层次链的产品装配过程建模方法[J].计算机集成制造系统,2009,15(8):1522-1527.
[5]刘丽兰[1],俞涛[1],施战备[1].制造网格中服务质量管理系统的研究[J].计算机集成制造系统,2005,11(2):284-288.
[6]萧毅鸿[1,2],周献中[1],朱亮[3],苏正炼[3],陆晓明[1].基于改进层级任务网络规划的Web服务自动组合[J].江苏大学学报：自然科学版,2012,33(1):77-82.
[7]宋泾舸[1],查建中[1],陆一平[1].基于虚拟装配体绑定的产品层次化装配序列生成[J].北京交通大学学报：自然科学版,2011,35(1):145-149.
[8]Xu Xun.From Cloud Computing to Cloud Manu-facturingCJ].Robotics and Computer-IntegratedManufacturing ,2011,2(1):75-86.
[9]Cardoso J?Sheth A,Miller J,et al.Quality of Servicefor Workflows and Web Service Processes[J].Jour-nal of Web Semantics,2004,1(3):281-308.
[10]李惠林[1,2],殷国富[1],谢庆生[2],牛鸣岐[2].面向网络化制造的制造资源组合评价方法研究[J].计算机集成制造系统,2008,14(5):955-961.
[11]何凤英[1].基于用户偏好的HTN规划在网格服务组合中的研究[J].福州大学学报：自然科学版,2010(1):14-19.
[12]陶飞[1,2],张霖[1,2],郭华[1,2],罗永亮[1,2],任磊[1,2].云制造特征及云服务组合关键问题研究[J].计算机集成制造系统,2011,17(3):477-486.
[13]陶飞,胡业发,张霖.制造网格资源服务优化配置理论与方法[M].北京:机械工业出版社,2010.
[14]邓水光[1],黄龙涛[1],尹建伟[1],李莹[1],吴健[1].Web服务组合技术框架及其研究进展[J].计算机集成制造系统,2011,17(2):404-412.
[15]刘丽兰[1],俞涛[1],施战备[1].制造网格中基于服务质量的资源调度研究[J].计算机集成制造系统,2005,11(4):475-480.
[16]刘卫宁,刘波,孙棣华.面向多任务的制造云服务组合研究[J/OL].计算机集成制造系统,2012[2012-03-16].http://www.cnki.net/kcms/detail/ll.3619.TP.20120201.1556.003.html.
[17]Liangzhao Zeng Benatallah B. Ngu A.H.H. Dumas M. Kalagnanam J. Chang H. . QoS-aware middleware for Web services composition [J]. 2004,5(5) .
[18]Fei Tao Yefa Hu Dongming Zhao Zude Zhou Haijun Zhang Zhenzhen Lei . Study on manufacturing grid resource service QoS modeling and evaluation [J]. 2009,9/10(9/10) .
[19]Fei Tao Yefa Hu Dongming Zhao Zude Zhou Haijun Zhang Zhenzhen Lei . 查看详情 [J]. 2009 .

Study on Hierarchical Service Composition in Cloud Manufacturing

基于层次化的云制造服务组合研究

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

[1]	LU Jianfeng, HAN Tiaojuan, YU Yaoping. Collaboration of Cloud Manufacturing Service Based on Service Choreography [J]. China Mechanical Engineering, 2021, 32(07): 849-859.
[2]	LI Yang, GUO Fei, LI Maoyuan, ZHANG Yun, LI Dequn. Intelligent Technology of Plastic Injection Molding and Its Applications [J]. China Mechanical Engineering, 2020, 31(22): 2734-2744.
[3]	LI Qiang, RU Ke, LIU Jiliang, ZHANG Ke. Interactive Cloud Manufacturing Mode for Mass Personalization [J]. China Mechanical Engineering, 2020, 31(07): 788-796.
[4]	GUO Jutao, HONG Haibo, ZHONG Keke, LIU Xiaojia, GUO Yu. Production Management and Control Method of Aerospace Manufacturing Workshops Based on Digital Twin [J]. China Mechanical Engineering, 2020, 31(07): 808-814.
[5]	HE Zheng;ZHANG Zhizhao;LI Bo. Evolutionary Game Model of Knowledge Transfer Incentive in Cloud Manufacturing Supply Chains [J]. China Mechanical Engineering, 2020, 31(06): 695-705.
[6]	QIU Shaolin;QIAN Lijun;LU Jianhui. Research on AVPS Based on Scenario Driven and Hierarchical Planning [J]. China Mechanical Engineering, 2019, 30(19): 2364-2371.
[7]	XIA Guang1,3;ZHANG Yang1,3;TANG Xiwen2;XIE Hai1,3;YANG Meng1,3;GAO Jun1,3. Research on Anti-rollover Hierarchical Control of Counterbalanced Forklifts [J]. China Mechanical Engineering, 2019, 30(17): 2066-2075.
[8]	GUAN Chao;ZHANG Zeqiang;ZHU Lixia;MAO Lili. A MINLP Model and Improved Simulated Annealing Algorithm for Double-layer Corridor Allocation Problem [J]. China Mechanical Engineering, 2019, 30(08): 975-983.
[9]	YANG Guoyong1,2;WANG Hongguang1;JIANG Yong1;LING Lie1. A Hierarchical and Simultaneous Gravity Unloading Testbed [J]. China Mechanical Engineering, 2019, 30(07): 818-824.
[10]	GONG Xiaorong, LI Xiaobin, YIN Chao. Optimization Decision Method of Machine Tool Resources Based on Bayesian Network under Cloud Manufacturing Environments [J]. China Mechanical Engineering, 2018, 29(20): 2438-2445.
[11]	HE Wei, JIA Guozhu, KONG Jili, ZONG Hengshan. Sustainability-based Multi-task Scheduling in Cloud Manufacturing [J]. China Mechanical Engineering, 2018, 29(18): 2215-2225.
[12]	LIU Yongkui, WANG Lihui, WANG Xi Vincent, XU Xun. A Revisit to Cloud Manufacturing [J]. China Mechanical Engineering, 2018, 29(18): 2226-2237.
[13]	DONG Yuanfa;WU Zhengjia;DU Xuan;ZHA Jing;YUAN Qingsong. Resource Abnormal Management Method of Unsteady Processes of Cloud Manufacturing Services [J]. China Mechanical Engineering, 2018, 29(10): 1193-1200.
[14]	LIU Xiaoyang;LIU Enfu;FANG Yixiang;LIU Zhenyu;JIN Jiangyan. Optimal Deployment of Networked Manufacturing Resources Based on TPS Hierarchical System [J]. China Mechanical Engineering, 2018, 29(07): 850-859.
[15]	WANG Qiucheng;WEI Ruihui;ZHANG Qijiong. Assessment of Carbon Emissions of Remanufacturing Processes of Used CVT [J]. China Mechanical Engineering, 2017, 28(18): 2224-2230,2267.