Resource service optimal-selection based on intuitionistic fuzzy set and non-functionality QoS in manufacturing grid system

  • Authors:

  • Fei Tao;Dongming Zhao;Lin Zhang

  • Affiliations:

  • Beihang University, School of Automation Science and Electrical Engineering, 100191, Beijing, People’s Republic of China and Wuhan University of Technology, Hubei Digital Manufacturing Key ...;The University of Michigan-Dearborn, Department of Electrical and Computer Engineering, 48128-1491, Dearborn, MI, USA;Beihang University, School of Automation Science and Electrical Engineering, 100191, Beijing, People’s Republic of China

  • Venue:
  • Knowledge and Information Systems
  • Year:
  • 2010

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Abstract

In manufacturing grid (MGrid) system, according to functional requirements of a task, there exist a lot of resource services which have similar functional characteristics. Multiple resource services with similar functional characteristics raise the concern over resource service optimal-selection (RSOS). It is important to select the optimal resource service according to their non-functionality characteristics or quality of service (QoS). However, QoS attributes are not easy to measure due to their complexity and involvement of ill-structured information. In this study, user’s feeling is taken into account in RSOS in an MGrid system. The non-functionality QoS evaluation of resource services is based on users’ feeling and transaction experiences using intuitionistic fuzzy set (IFS). Furthermore, the dynamics of non-functionality QoS is considered, and a time-decay function is introduced into non-functionality QoS evaluation. A new method is proposed for RSOS based on IFS and non-functionality QoS, and the procedures are presented in detail. A practice case study is used to illustrate the proposed method and procedure. The performance and advantage of the proposed method are discussed.