Service composition model and method in cloud manufacturing

Robotics and Computer-Integrated Manufacturing - Tập 61 - Trang 101840 - 2020
Minghai Yuan1, Zhuo Zhou1, Xianxian Cai1, Chao Sun1, Wenbin Gu1
1College of Mechanical and Electrical Engineering, Hohai University, Changzhou, China

Tài liệu tham khảo

Lu, 2019, Cloud-based manufacturing equipment and big data analytics to enable on-demand manufacturing services, Robot. Cim-Int. Manuf., 57, 92, 10.1016/j.rcim.2018.11.006 Pisching, 2015, Service composition in the cloud-based manufacturing focused on the industry 4.0, IFIP Adv. Inf. Commun. Technol., 450, 65, 10.1007/978-3-319-16766-4_7 H.Bouzary, 2018, Service optimal selection and composition in cloud manufacturing: a comprehensive survey, Int. J. Adv. Manuf. Technol., 97, 795, 10.1007/s00170-018-1910-4 Liu, 2018, An approach for service composition optimisation considering service correlation via a parallel max-min ant system based on the case library, Int. J. Comput. Integr. Manuf., 31, 1147 Ren, 2018, Manufacturing service composition model based on synergy effect: a social network analysis approach, Appl. Soft. Comput, 70, 288, 10.1016/j.asoc.2018.05.039 Jin, 2017, Correlation-aware QoS modeling and manufacturing cloud service composition, J. Intell. Manuf., 28, 1947, 10.1007/s10845-015-1080-2 Z.Zhang, 2018, Manufacturing service composition self-adaptive approach based on dynamic matching network, J. Softw., 29, 3355 Chang, 2017 Xue, 2016, Manufacturing service composition method based on networked collaboration mode,, J. Netw. Comput. Appl., 59, 28, 10.1016/j.jnca.2015.05.003 Fazeli, 2019, An ensemble optimisation approach to service composition in cloud manufacturing, Int. J. Comput. Integr. Manuf., 32, 83, 10.1080/0951192X.2018.1550679 Zhu, 2019, IHDETBO: a novel optimization method of multi-batch subtasks parallel-hybrid execution cloud service composition for cloud manufacturing, Complexity, 2019, 10.1155/2019/7438710 Xu, 2018, Self-adaptive bat algorithm for large scale cloud manufacturing service composition, Peer-to-Peer Netw. Appl., 11, 1115, 10.1007/s12083-017-0588-y Li, 2018, An approach to IoT service optimal composition for mass customization on cloud manufacturing, IEEE ACCESS, 6, 50572, 10.1109/ACCESS.2018.2869275 Puttonen, 2016, Cloud computing as a facilitator for web service composition in factory automation, J. Intell. Manuf., 30, 687, 10.1007/s10845-016-1277-z Zhou, 2018, An adaptive multi-population differential artificial bee colony algorithm for many-objective service composition in cloud manufacturing, Inf. Sci., 456, 50, 10.1016/j.ins.2018.05.009 Li, 2016, Composition of resource-service chain for cloud manufacturing, IEEE T. Ind. Inform., 12, 211, 10.1109/TII.2015.2503126 Ghobaei-Arani, 2018, CSA-WSC: cuckoo search algorithm for web service composition in cloud environments, Soft Comput, 22, 8353, 10.1007/s00500-017-2783-4 Seghir, 2018, A hybrid approach using genetic and fruit fly optimization algorithms for qos-aware cloud service composition, J. Intell. Manuf., 29, 1773, 10.1007/s10845-016-1215-0 Li, 2016, Multi-objective optimization of cloud manufacturing service composition with cloud-entropy enhanced genetic algorithm, Strojniski vestnik-J. Mech. Eng., 62, 577 Zhou, 2017, Multi-population parallel self-adaptive differential artificial bee colony algorithm with application in large-scale service composition for cloud manufacturing, Appl. Soft. Comput., 56, 379, 10.1016/j.asoc.2017.03.017 Lartigau, 2015, Cloud manufacturing service composition based on QoS with geo-perspective transportation using an improved artificial bee colony optimisation algorithm, Int. J. Prod. Res, 53, 4380, 10.1080/00207543.2015.1005765 Zhou, 2017, Multi-objective hybrid artificial bee colony algorithm enhanced with lévy flight and self-adaption for cloud manufacturing service composition, Appl Intell, 47, 721, 10.1007/s10489-017-0927-y Xu, 2016, A fuzzy operator based bat algorithm for cloud service composition, Int. J. Wirel. Mob. Comput., 11, 42, 10.1504/IJWMC.2016.079471 Xiang, 2014, QoS and energy consumption aware service composition and optimal-selection based on pareto group leader algorithm in cloud manufacturing system, Cent Eur J Oper Res., 22, 663, 10.1007/s10100-013-0293-8 Xiang, 2016, The case-library method for service composition and optimal selection of big manufacturing data in cloud manufacturing system, Int. J. Adv. Manuf. Technol., 84, 59, 10.1007/s00170-015-7813-8 Liu, 2017, Workload-based multi-task scheduling in cloud manufacturing, Robot. Cim-Int. Manuf., 45, 3, 10.1016/j.rcim.2016.09.008 Wang, 2018, Urgent task-aware cloud manufacturing service composition using two-stage biogeography-based optimisation, Int. J. Comput. Integr. Manuf., 31, 1034, 10.1080/0951192X.2018.1493230 Li, 2017, A clustering network-based approach to service composition in cloud manufacturing, Int. J. Comput. Integr. Manuf., 30, 1331, 10.1080/0951192X.2017.1314015 Yuan, 2017, Manufacturing resource modeling for cloud manufacturing, Int. J. Intell. Syst., 32, 414, 10.1002/int.21867 Lu, 2017, A semantic web-based framework for service composition in a cloud manufacturing environment,, J. Manuf. Syst., 42, 69, 10.1016/j.jmsy.2016.11.004 Xu, 2012, From cloud computing to cloud manufacturing, Robot. Cim-Int. Manuf., 28, 75, 10.1016/j.rcim.2011.07.002 Liu, 2017, An approach for multipath cloud manufacturing services dynamic composition, Int. J. Intell. Syst., 32, 371, 10.1002/int.21865 Yu, 2016, 47