IoT-enabled dynamic service selection across multiple manufacturing clouds

被引：27
作者：
Yang C. [1 ]
Shen W. [1 ]
Lin T. [2 ]
Wang X. [1 ]
机构：
[1] Department of Electrical and Computer Engineering, University of Western Ontario, London, ON
[2] Beijing Simulation Center, Beijing
来源：
Yang, Chen (wzhyoung@gmail.com) | 2016年 / Elsevier Ltd卷 / 07期
关键词：
Cloud manufacturing; Internet of Things; Multiple manufacturing clouds; Service selection; Uncertainty;
D O I：
10.1016/j.mfglet.2015.12.001
中图分类号：
学科分类号：
摘要：
Cloud manufacturing can manage mass manufacturing resources and capabilities, and provide them as services via the Internet. Undoubtedly, multiple manufacturing clouds (MCs) will have extremely abundant services in terms of function, price, reliability, location, etc. Selecting and using services from multiple MCs is a natural evolution in the best interests of service consumers. On the other side, various uncertainties in today's highly-dynamic business environment can easily disrupt manufacturing activities, rendering original schedules obsolete. However, little work has been done to take advantages of abundant services from MCs and to effectively deal with uncertainties. To address this requirement, we propose a dynamic service selection (SS) method across multiple MCs. The proposed method uses IoT's real-time sensing ability on service execution, Big-Data's knowledge extraction ability on services in MCs, and event-driven dynamic SS optimization to deal with disturbances from users and service market and to continuously adjust SS to be more effective and efficient. © 2015 Society of Manufacturing Engineers (SME).
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页码：22 / 25
页数：3
相关论文
共 12 条
  • [1] Li B.H., Zhang L., Wang S.L., Tao F., Cao J.W., Jiang X.D., Et al., Cloud manufacturing: a new service-oriented networked manufacturing model, Comput Integr Manuf Syst, 16, pp. 1-7, (2010)
  • [2] He W., Xu L., A state-of-the-art survey of cloud manufacturing, Int J Comput Integr Manuf, 28, pp. 239-250, (2015)
  • [3] Gao J., Yao Y.L., Zhu V.C.Y., Sun L.Y., Lin L., Service-oriented manufacturing: a new product pattern and manufacturing paradigm, J Intell Manuf, 22, pp. 435-446, (2011)
  • [4] Tao F., Zhang L., Liu Y., Cheng Y., Wang L., Xu X., Manufacturing service management in cloud manufacturing: overview and future research directions, J Manuf Sci Eng, 137, pp. 40912-40923, (2015)
  • [5] Tao F., Zhao D., Hu Y.F., Zhou Z., Correlation-aware resource service composition and optimal-selection in manufacturing grid, Eur J Oper Res, 201, pp. 129-143, (2010)
  • [6] Zeng L., Benatallah B., Ngu A.H.H., Dumas M., Kalagnanam J., Chang H., Qos-aware middleware for web services composition, IEEE Trans Software Eng, 30, pp. 311-327, (2004)
  • [7] Huang S., Zeng S., Fan Y., Huang G., Optimal service selection and composition for service-oriented manufacturing network, Int J Comput Integr Manuf, 24, pp. 416-430, (2011)
  • [8] Ouelhadj D., Petrovic S., A survey of dynamic scheduling in manufacturing systems, J Sched, 12, pp. 417-431, (2009)
  • [9] Ardagna D., Di Nitto E., Casale G., Petcu D., Mohagheghi P., Mosser S., Et al., Modaclouds: a model-driven approach for the design and execution of applications on multiple clouds., In: Proceedings of the 4th international workshop on modeling in software engineering. IEEE, pp. 50-56, (2012)
  • [10] Herroelen W., Leus R., Project scheduling under uncertainty: survey and research potentials, Eur J Oper Res, 165, pp. 289-306, (2005)
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