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

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.

[1]  Germano Resconi,et al.  Agents’ model of uncertainty , 2008, Knowledge and Information Systems.

[2]  Dazhe Zhao,et al.  Manufacturing Grid: Needs, Concept, and Architecture , 2003, GCC.

[3]  Miin-Shen Yang,et al.  On similarity measures between intuitionistic fuzzy sets , 2008 .

[4]  W.M.P. van der Aalst,et al.  Don't go with the flow: web services composition standards exposed , 2003 .

[5]  Jianwen Su,et al.  Web service discovery based on behavior signatures , 2005, 2005 IEEE International Conference on Services Computing (SCC'05) Vol-1.

[6]  Gero Mühl,et al.  QoS aggregation in Web service compositions , 2005, 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service.

[7]  Sam Chung,et al.  Community-Based Service Discovery , 2006, 2006 IEEE International Conference on Web Services (ICWS'06).

[8]  Valérie Issarny,et al.  Context-aware service discovery in heterogeneous networks , 2005, Sixth IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks.

[9]  Zeshui Xu,et al.  Dynamic intuitionistic fuzzy multi-attribute decision making , 2008, Int. J. Approx. Reason..

[10]  Wei-Guo Zhang,et al.  On weighted lower and upper possibilistic means and variances of fuzzy numbers and its application in decision , 2009, Knowledge and Information Systems.

[11]  Fei Tao,et al.  Study on manufacturing grid resource service QoS modeling and evaluation , 2009 .

[12]  Tomas Vitvar,et al.  Dynamic Service Discovery Through Meta-interactions with Service Providers , 2007, ESWC.

[13]  Lothar Litz,et al.  Learning Premises of Fuzzy Rules for Knowledge Acquisition in Classification Problems , 2002, Knowledge and Information Systems.

[14]  Minghua Chen,et al.  Quality Driven Web Services Composition Based on an Extended Layered Graph , 2008, 2008 International Conference on Computer Science and Software Engineering.

[15]  Abdelsalam Helal,et al.  Context attributes: an approach to enable context-awareness for service discovery , 2003, 2003 Symposium on Applications and the Internet, 2003. Proceedings..

[16]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[17]  Punam Bedi,et al.  Trust Based Recommender System for Semantic Web , 2007, IJCAI.

[18]  James A. Hendler,et al.  Filtering and selecting semantic Web services with interactive composition techniques , 2004, IEEE Intelligent Systems.

[19]  Huaimin Wang,et al.  Quality driven Web services selection , 2005, IEEE International Conference on e-Business Engineering (ICEBE'05).

[20]  Christos Doulkeridis,et al.  Context-based caching and routing for P2P web service discovery , 2007, Distributed and Parallel Databases.

[21]  Gero Mühl,et al.  QoS aggregation for Web service composition using workflow patterns , 2004 .

[22]  Robin Qiu Manufacturing grid: a next generation manufacturing model , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[23]  L. Zadeh A Fuzzy-Set-Theoretic Interpretation of Linguistic Hedges , 1972 .

[24]  Ping Wang,et al.  QoS-aware web services selection with intuitionistic fuzzy set under consumer's vague perception , 2009, Expert Syst. Appl..

[25]  Chi-Chun Lo,et al.  Fuzzy Consensus on QoS in Web Services Discovery , 2006, 20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06).

[26]  Zeshui Xu,et al.  Some similarity measures of intuitionistic fuzzy sets and their applications to multiple attribute decision making , 2007, Fuzzy Optim. Decis. Mak..

[27]  Hans-Peter Schwefel,et al.  Context-Sensitive Service Discovery Experimental Prototype and Evaluation , 2007, Wirel. Pers. Commun..

[28]  Rajkumar Buyya,et al.  A Market-Oriented Grid Directory Service for Publication and Discovery of Grid Service Providers and their Services , 2006, The Journal of Supercomputing.

[29]  Bin Yu,et al.  Grid Service Discovery with Rough Sets , 2008, IEEE Transactions on Knowledge and Data Engineering.

[30]  Fei Tao,et al.  Study on resource service match and search in manufacturing grid system , 2009 .

[31]  Daniel A. Menascé,et al.  Composing Web Services: A QoS View , 2004, IEEE Internet Comput..

[32]  Stijn Heymans,et al.  Two-Phase Web Service Discovery Based on Rich Functional Descriptions , 2007, ESWC.

[33]  Fei Tao,et al.  Study on manufacturing grid & its resource service optimal-selection system , 2008 .

[34]  Hao Wang,et al.  Solving QoS-driven Web service dynamic composition as fuzzy constraint satisfaction , 2005, 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service.

[35]  Andrea Zisman,et al.  UML-Based Service Discovery Framework , 2006, ICSOC.

[36]  Ranjit Biswas,et al.  Some operations on intuitionistic fuzzy sets , 2000, Fuzzy Sets Syst..

[37]  Xing Zhang,et al.  A composite service selection algorithm based on structural model , 2009, 2009 International Conference on Machine Learning and Cybernetics.

[38]  Steffen Staab,et al.  Web Services: Been There, Done That? , 2003, IEEE Intell. Syst..

[39]  Frank van Harmelen,et al.  Expertise-based peer selection in Peer-to-Peer networks , 2008, Knowledge and Information Systems.

[40]  Vincenzo D'Andrea,et al.  Web Service Discovery Based on Past User Experience , 2007, BIS.

[41]  Xiaolong Wang,et al.  Optimal resource allocation on grid systems for maximizing service reliability using a genetic algorithm , 2006, Reliab. Eng. Syst. Saf..

[42]  Fei Tao,et al.  Application and modeling of resource service trust-QoS evaluation in manufacturing grid system , 2009 .

[43]  Sascha Ossowski,et al.  A Role-Based Support Mechanism for Service Description and Discovery , 2007, SOCASE.

[44]  Chi-Chun Lo,et al.  Fuzzy Similarity Clustering for Consumer-Centric QoS-Aware Selection of Web Services , 2008, 2009 International Conference on Complex, Intelligent and Software Intensive Systems.

[45]  Xiaoyun Zhang,et al.  Conception and implementation of a collaborative manufacturing grid , 2007 .