Resource Service Management in Manufacturing Grid System

ISBN-13: 9781118122310 / Angielski / Twarda / 2012 / 550 str.

Zhifeng (Jeffrey) Tao

Opis

This book includes discussion on advance computer technologies such as cloud computing, grid computing, and service computing. In addition, it furthers the theory and technology of grid technologies that is used in manufacturing, and accelerates the development of service-oriented manufacturing.

Spis treści

1. Introduction of Manufacturing Grid 1

2. Resource Service Optimal–Allocation System in MGrid 27

3. Digital Description of MGrid Resource Service 43

4. MGrid Resource Service Match and Search 75

5. Resource Service QoS Modeling and Evaluation 115

6. Resource Service Trust–QoS Evaluation 143

7. Resource Service Optimal–selection and Composition 190

8. Resource Service Optimal–selection Based on Intuitionistic Fuzzy Set and Non–functionality QoS 215

9. Correlation Relationship Management in Resource Services Composition 253

10. Resource Service Composition Optimal–selection 275

11. Resource Services Composition Flexibility 311

12. Resource Services Composition Network 357

13. Failure Detection and Recovery in Resource Service Optimal–Allocation 403

14. Summary of the Application of Grid Technology in Manufacturing 435

15. Cloud Manufacturing: Development and Commerce Realization of MGrid 469

O autorze

Fei Tao is currently an associate professor at the Beihang University of Aeronautics and Astronautics. He obtained his PhD in mechanical engineering from Wuhan University of Technology, China, in 2008. He was elected a research affiliate of CIRP, The International Academy for Production Engineering, in 2009. Dr. Tao is the founder and editor–in–chief of International Journal of Service and Computing Oriented Manufacturing.

Lin Zhang received his PhD in 1992 from the Department of Automation at Tsinghua University, China. He is a full professor at Beihang University, the Vice President of Chinese Association for System Simulation, and a member of the council of Chinese Association for Artificial Intelligence.

Yefa Hu received his PhD in mechanical design and theory from Wuhan University of Technology (WHUT) in 2001. He is a full professor at the School of Mechanical and Electronic Engineering at WHUT. He has published two books on "Magnetic Suspension Technology" and "Manufacturing Grid," as well as more than sixty refereed international and domestic papers.

Blurb

The aim of this book is to make advanced computing technologies (service, grid and cloud computing) to be fully used in manufacturing so as to enhance the utilization and sharing of manufacturing resources, and to speed up the transformation from production–oriented manufacturing to service–oriented manufacturing.

Resource Service Management in Manufacturing Grid System constructs a concrete theory for MGrid and presents implementation methods for MGrid resources and services.

Specifically, the book:

Breaks through the application research field of grid technology, turning grid technology from traditional large–scale science computing to application in manufacturing.

Establishes the theoretical foundation for MGrid Resource Service Optimal Allocation (RSOA). From the perspectives of manufacturing science, systematics, ontology, fuzzy mathematics, information theory, set theory, and social psychology, the book explains the basic theory and the implementation method for addressing MGrid RSOA in many aspects such as implementation framework of RSOA, digital description, match and search, quality of service modeling and evaluation, optimal–selection, composition of resource service, and resource service combination network, failure detection and recovery of RSOA.

Provides relevant theories and methods of MGrid RSOA, such as resource service match and search, QoS evaluation, optimal selection, composition, and failure–tolerance management. The theories can be used not only in addressing the RSOA problem in MGrid, but also in resolving the RSOA problem in other related SOA–based distributed systems.

Audience

Policymakers, executives, academics, educators, researchers, and practitioners/engineers working in the interdisciplinary fields of manufacturing, information technology/computer science, operational research, simulation, industrial informatics and management science.