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A fuzzy QoS-aware resource service selection considering design preference in cloud manufacturing system

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Abstract

Cloud manufacturing (CMfg) is a kind of advanced service-oriented manufacturing model with on-demand use of various lifecycle-resources. Resource service selection (RSS) is one of the critical techniques for implementing CMfg, which is applied for building flexible and loosely coupled service application to requestors. With lots of resource services owning similar functionality in RSS, quality of service (QoS) which can reflect user experience of service is often considered as a key technology to distinguish resource services for RSS. However, because of the heterogeneous QoS values, vast amounts of homogeneous resources and dynamic customer requirements in CMfg, the issue of how to measure fuzzy QoS and select the best services considering design preference, are rarely studied in CMfg. In this paper, we propose an integrated resource service selection approach to assist requesters to obtain optimal manufacturing services. Firstly, the problem description on resource service selection in CMfg is summarized. Then, a design preference-based QoS description model of CMfg is proposed and a QoS computation model based on fuzzy theory is presented for QoS measurement. Based on the above model, particle swarm optimization (PSO) algorithm is adopted to select the optimal service composition. Finally, a numerical example is given to validate the effectiveness and efficiency of the proposed approach.

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Authors and Affiliations

  1. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, 310027, People’s Republic of China

    Hao Zheng, Yixiong Feng & Jianrong Tan

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  1. Hao Zheng
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  2. Yixiong Feng
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  3. Jianrong Tan
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Correspondence to Yixiong Feng.

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Zheng, H., Feng, Y. & Tan, J. A fuzzy QoS-aware resource service selection considering design preference in cloud manufacturing system. Int J Adv Manuf Technol 84, 371–379 (2016). https://doi.org/10.1007/s00170-016-8417-7

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  • DOI: https://doi.org/10.1007/s00170-016-8417-7

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