Resource Service Management in Manufacturing Grid System -- Contents -- Acknowledgements -- Preface -- Abbreviations -- 1 Introduction to Manufacturing Grid -- 1.1 Introduction -- 1.2 Proposal of Manufacturing Grid -- 1.2.1 Several Issues of Manufacturing -- 1.2.2 Proposal of MGrid -- 1.2.3 Technological Driving Forces of MGrid -- 1.3 Concept of MGrid -- 1.3.1 A Brief Outline of Grid and its Applications -- 1.3.2 Concept of MGrid -- 1.4 Basic Features of MGrid -- 1.5 The Connotation of MGrid -- 1.6 Comparison between MGrid and Networked Manufacturing -- 1.7 Comparison between MGrid and Computing Grid -- 1.8 Key Research Contents and Technologies of MGrid -- 1.8.1 General Technologies -- 1.8.2 Supporting Technologies -- 1.8.3 Key Enabling Technologies -- 1.8.4 Application Technologies -- 1.9 Summary -- 2 Resource Service Optimal-Allocation System in MGrid -- 1.1 Introduction -- 2.2 The Architecture of MGrid -- 2.2.1 MGrid Resource Layer -- 2.2.2 MGrid Core Middleware Layer -- 2.2.3 MGrid User Service Middleware Layer -- 2.2.4 MGrid User Portal Layer -- 2.2.5 MGrid User Layer -- 2.3 MGrid Collaborative Manufacturing Platform -- 2.3.1 Conceptual Model of MGrid Collaborative Manufacturing Platform -- 2.3.2 Resource Service Publication -- 2.3.3 The Resource Service Exchange between RSP and RSD -- 2.4 MGrid Resource Service Optimal-Allocation System (MGRSOAS) -- 2.5 The Key Issues and Technologies for Realizing RSOAS -- 2.5.1 Modeling and Digital Description of Resource Service (DDoRS) -- 2.5.2 Resource Service Match and Search (RSMS) -- 2.5.3 QoS Modeling and Evaluation of Resource Service -- 2.5.4 MGrid Resource Service Optimal-Selection and Composition (RSOSC) -- 2.5.5 Resource Service Composition and Network Modeling and Dynamic Characteristics -- 2.5.6 Failure Tolerance Management -- 2.6 Summary -- 3 Digital Description of MGrid Resource Service.

3.1 Introduction -- 3.2 Classification of MGrid Resource Service and Its Application -- 3.2.1 Classification of MGrid Resource and Resource Service -- 3.2.2 Application Case: Resource Service Design for Magnetic Bearing System -- 3.3 Requirements of DDoRS in MGrid -- 3.4 MGrid and Ontology -- 3.5 Establishing the Method of MGrid-Ontology -- 3.5.1 Step 1: Define the Scope and Requirements of MGrid-Ontology -- 3.5.2 Step 2: Determine Essential Concepts, Reusing Existing Ontologies if Possible -- 3.5.3 Step 3: Analyses and Design of MGrid-Ontology -- 3.5.4 Step 4: Representation of MGrid-Ontology -- 3.5.5 Step 5: Verification and Validation of MGrid-Ontology -- 3.6 Selection of Describing Language for MGrid-Ontology -- 3.7 MGrid Ontology -- 3.7.1 OWL-S -- 3.7.2 MGrid-Ontology -- 3.8 DDoRS Based on MGrid-Ontology -- 3.8.1 Description of Agent -- 3.8.2 Description of MGSP -- 3.8.3 Description of MGSM -- 3.9 Application Case: MGrid-Ontology Based MGrid Resource Service Discovery -- 3.10 Summary -- 4 MGrid Resource Service Match and Search -- 4.1 Introduction -- 4.2 Related Works -- 4.2.1 Service Discovery in Traditional Distributed System -- 4.2.2 Service Match and Discovery in Distributed Manufacturing System -- 4.3 Framework of Resource Service Match and Search in MGrid -- 4.4 SMAs: Similarity Matching Algorithms (SMAs) -- 4.4.1 Word Matching Algorithms (WMAs) -- 4.4.2 Sentence Matching Algorithms (SeMAs) -- 4.4.3 Number Matching Algorithms (NMAs) -- 4.4.4 Entity Class Matching Algorithms (ECMAs) -- 4.5 RS-Matcher: Resource Service Matcher -- 4.5.1 Basic-matching -- 4.5.2 I/O-matching -- 4.5.3 QoS-matching -- 4.5.4 Integrated-matching -- 4.6 Case Study -- 4.6.1 Step 1: Basic-matching -- 4.6.2 Step 2: I/O-matching -- 4.6.3 Step 3: QoS-matching -- 4.6.4 Step 4: Integrated-matching -- 4.7 Performance Results and Discussion -- 4.7.1 Accuracy.

4.7.2 Efficiency -- 4.8 Summary -- 5 Resource Service QoS Modeling and Evaluation -- 5.1 Introduction -- 5.2 Related Works -- 5.3 Evaluation Indices System of MGrid Resource Service -- 5.4 Evaluation of SEIs and IEIs -- 5.4.1 Evaluation Framework of SEIs and IEIs -- 5.4.2 Structure Model of Agent -- 5.4.3 Evaluation Process of SEIs and IEIs -- 5.4.3.1 Setting of Manufacturing Resources Evaluation Indexes Set U -- 5.4.3.2 Setting the Evaluation Grade Values Set P -- 5.4.3.3 Establishment of the Comprehensive Information Matrix R -- 5.3.3.4 Establishment of the Weight Coefficients Set Q -- 5.4.3.5 Establishment of the Comprehensive Evaluation Matrix M -- 5.4.3.6 Establishment of the Increased Weight Set Matrix B -- 5.4.3.7 The Result of Comprehensive Evaluation Quantitative Value V Based on Matrix M and Matrix B -- 5.5 Classification and Modeling of MGrid QoS -- 5.5.1 QoS Modeling from the Whole-lifecycle Management of MGrid Resource Service QoS -- 5.5.2 QoS Modeling from MGrid Architecture Views -- 5.5.3 MGrid QoS Attribute Parameters Modeling -- 5.6 Evaluation of MGrid QoS Attribute Parameter -- 5.6.1 Time -- 5.6.2 Cost -- 5.6.3 Reliability -- 5.6.4 Maintainability -- 5.6.5 Trust-QoS -- 5.6.6 Function Similarity -- 5.7 Application Case: QoS-based MGrid Resource Service Management -- 5.8 Summary -- 6 Resource Service Trust-QoS Evaluation -- 6.1 Introduction -- 6.2 Related Works -- 6.2.1 MGrid Resource Scheduling Based on QoS -- 6.2.2 QoS and Trust-QoS -- 6.3 Resource Management and Trust Relationship Management in MGrid -- 6.4 MGrid Resource Service Trust-QoS Relationship Model -- 6.5 MGrid Resource Service Trust-QoS Evaluation Model -- 6.5.1 Related Conceptions and Definitions -- 6.5.2 Intra-domain Trust-QoS Evaluation Model of Resource Service -- 6.5.3 Inter-domain Trust-QoS Evaluation Model of Resources Service -- 6.6 Data Structure Design.

6.7 Trust-QoS Evaluating and Updating Algorithms -- 6.7.1 Direct Trust-QoS Evaluating Algorithm -- 6.7.2 Recommended Trust-QoS Evaluating Algorithm -- 6.7.3 Comprehensive Combining Recommended Trust-QoS Evaluating Algorithm -- 6.8 Real-time and Dynamical Updating Algorithm of Trust-QoS Degree -- 6.9 Trust-QoS Evaluation Case Study -- 6.10 Application Case: Trust-QoS Based MGrid Resource Service Scheduling -- 6.10.1 Requirements of Trust-QoS Based MGrid Resource Service Scheduling -- 6.10.2 Trust-QoS Based MGrid Resource Service Scheduling Framework -- 6.10.3 Trust-QoS Based MGrid Resource Service Scheduling Algorithms -- 6.11 Summary -- 7 Resource Service Optimal-selection and Composition Framework -- 7.1 Introduction -- 7.2 MGrid-RSOSCF: MGrid Resource Service Optimal-selection and Composition -- 7.2.1 Architecture of MGrid-RSOSCF -- 7.2.2 Life-cycle of MGrid Resource Service Composition -- 7.3 T-Layer: Task Layer -- 7.3.1 Basic Models of MGrid Task -- 7.3.2 Main Functions and Services in T-Layer -- 7.4 S-Layer: Resource Service Match and Search Layer -- 7.5 Q-Layer: Resource Service QoS Synthetically Processing Layer -- 7.5.1 Main Functions and Services in Q-Layer -- 7.5.2 QoS Extraction -- 7.5.3 QoS Comparison -- 7.6 O-Layer: Resource Service Optimal-selection Layer -- 7.6.1 Simple Resource Service Optimal-selection Method -- 7.6.2 The Other Resource Service Optimal-selection Methods -- 7.7 C-Layer: Resource Service Composition Layer -- 7.7.1 RSC-Engine: Resource Service Composition Engine -- 7.7.2 RSCEP-Generator -- 7.7.3 RSCEP-Selector -- 7.7.4 RSCE-Controller: Resource Service Composition Executing Controller -- 7.7.5 RSC-Monitor: Resource Service Composition Monitor -- 7.7.6 RSC-Coordinator: Resource Service Composition Coordinator -- 7.8 Summary.

8 Resource Service Optimal-selection Based on Intuitionistic Fuzzy Set and Non-functionality QoS -- 8.1 Introduction -- 8.2 Framework of Resource Service Selection -- 8.3 Resource Service Optimal-selection Based on IFS in MGrid -- 8.3.1 Symbols and Notations -- 8.3.2 Preliminaries on Intuitionistic Fuzzy Set (IFS) -- 8.3.3 RSOS Based on IFS -- 8.3.3.1 Evaluating cj of RSm at Time Periods tk -- 8.3.3.2 Calculating the Synthetic Evaluation of Cj of RSm form t0 to tc -- 8.3.3.3 Determining the Weights of QoS Criteria -- 8.3.3.4 Evaluating Fuzzy Synthetic of Each CRS -- 8.3.3.5 Calculating the Closeness Coefficient of Each CRS -- 8.3.3.6 Ranking the Order of Candidate Resource Services (CRSs) -- 8.3.4 Data Structure Design -- 8.4 Case Study -- 8.4.1 Step 1: Extracting the Related Data of RS1, RS2, RS3, RS4, and RS5 -- 8.4.2 Step 2: Evaluating the QoS Criteria of Each Candidate Resource Service at Different Time Periods -- 8.4.3 Step 3: Calculating the Synthetic QoS Criteria of Each Candidate Resource Service -- 8.4.4 Step 4: Determining the Weights of Each QoS Criterion -- 8.4.5 Step 5: Calculating the Closeness Coefficient of Each CRS -- 8.4.6 Step 6: Ranking the Order of CRSs -- 8.5 Performance Analysis and Discussion -- 8.5.1 Scalability and Efficiency -- 8.5.2 Effectiveness -- 8.5.3 Comparison with the Method of Bedi (Bedi et al, 2007) -- 8.6 Summary -- 9 Correlation Relationship Management in Resource Services Composition -- 9.1 Introduction -- 9.2 Related Works -- 9.3 Motivation -- 9.4 Correlation Relationship among Resource Services -- 9.4.1 Combinable Correlation -- 9.4.1.1 Definition and Model -- 9.4.1.2 Combinable Correlation Degree -- 9.4.2 Business Entity Correlation -- 9.4.3 Statistical Cooperate Correlation -- 9.5 QoS Computation Model of Correlation-aware Resource Services Composition.

9.6 Case Study: Correlation-aware Resource Services Composition.