Computer science Books

Book SynopsisThis book focuses on Service Oriented Architecture (SOA), the basis of sustainable and more agile IT systems that are able to adapt themselves to new trends and manage processes involving a third party. The discussion is based on the public Praxeme method and features a number of examples taken from large SOA projects which were used to rewrite the information systems of an insurance company; as such, decision-makers, creators of IT systems, programmers and computer scientists, as well as those who will use these new developments, will find this a useful resource.Table of ContentsAcknowledgements xiii Foreword xv Preface xxi Guide for the Reader xxvii Introduction to the SOA Project at SMABTP xxxi Chapter 1. Initial Perspectives 1 1.1. 50 years of computing – an overview 1 1.2. What remains today? 5 Part I. Why a Sustainable Information System? 7 Chapter 2. Company-oriented Services 9 2.1. Consequences of the Internet revolution 9 2.2. What do the leading market players say? 12 2.3. What do the chief information officers think? 14 2.4. The issues faced at general management level 14 2.5. Levels of maturity 16 Chapter 3. SOA Maturity Levels 21 3.1. Towards the creation of a more agile information system 21 3.2. Cosmetic SOA 23 3.3. Extended SOA 24 3.4. Overhaul SOA 26 3.5. The matrices of SOA maturity 28 3.5.1. The matrix showing the definitions of SOA 28 3.5.2. The matrix showing the quality criteria of SOA 29 3.5.3. The matrix showing the strengths and weaknesses of SOA 29 Chapter 4. Economic and Social Aspects 31 4.1. Removal of obstacles that may slow down the progressive overhaul of an information system 32 4.2. The future of IT specialists 33 4.3. Off-shoring 33 4.4. The generation mix 34 4.5. The role of software infrastructure editors 35 Part II. The Principles of SOA 37 Chapter 5. The Properties of SOA 39 5.1. The definition of service for users 41 5.1.1. The user of the service 42 5.1.2. A business ambiguity 42 5.1.3. An example of a business service 43 5.2. The definition of service for IT specialists 44 5.2.1. The granularity of service 44 5.2.2. The separation of concerns 46 5.2.3. The service categories 47 5.2.4. Batch services 49 5.3. The properties of basic SOA 50 5.3.1. Loose coupling 50 5.3.2. Communication by messages 51 5.3.3. Design by contract 52 5.3.4. The limits of the basic properties 56 5.4. The properties of agility 56 5.4.1. The difference between the version and the variant of a service 58 5.4.2. Agility of the data 60 5.4.3. Agility of the rules 65 5.4.4. Agility of the processes 66 5.4.5. Agility of the human–computer interface 67 Chapter 6. Orchestration (BPM and SOA) 69 6.1. Multiple requirements in orchestration 71 6.1.1. Orchestration and SOA maturity levels 71 6.1.2. Functional requirements 73 6.1.3. Technical requirements 75 6.1.4. Enterprise architecture requirements 77 6.2. The levels of orchestration 78 6.2.1. Orchestration at the process level 79 6.2.2. Orchestration at screen level 80 6.2.3. Orchestration at the micro-process level (use cases) 81 6.2.4. Orchestration at the business service level 82 6.2.5. Orchestration between domains through the use of ESB 83 6.2.6. The orchestration of batches 83 6.3. The techniques of orchestration 85 6.3.1. The BPM engine 85 6.3.2. The business rules engine 86 6.3.3. Specific programming 86 6.4. Towards the homogenization of orchestration 87 6.4.1. Unified modeling 87 6.4.2. Unified standard 89 6.5. The benefits of orchestration 91 6.5.1. Advantages 91 6.5.2. Disadvantages 91 Part III. The Need for an Enterprise Method 93 Chapter 7. The Discovery of Services (Reference Framework and Urbanization) 95 7.1. New needs for the information system 96 7.1.1. Expansiveness and progressiveness 97 7.1.2. Mobilizing the many different competences 98 7.2. Why are different methods seldom used within companies? 98 7.3. Reference frameworks 101 7.3.1. Zachman’s framework 101 7.3.2. TOGAF 102 7.3.3. Peter Herzum’s framework 103 7.3.4. Important information to be taken from the reference frameworks 104 7.4. Essential tools 105 7.4.1. UML (Unified Modeling Language) 105 7.4.2. MDA (Model Driven Architecture) 106 7.4.3. Urbanization of the information system 107 Chapter 8. The Praxeme Enterprise Method 111 8.1. Praxeme: the initiative behind a public method 112 8.2. The Praxeme method 112 8.2.1. Product 113 8.2.2. Process 113 8.2.3. Procedures 114 8.2.4. Combining the three dimensions114 8.3. Enterprise system topology according to the Praxeme method 115 8.3.1. Upstream models 115 8.3.2. Logical (SOA), technical and software architecture models 117 8.3.3. Hardware and physical architecture models 117 8.3.4. Enterprise system topology 118 8.3.5. Pre-modeling 119 8.4. What the Praxeme method means for SOA 120 8.4.1. How can we find the correct services? 120 8.4.2. The link between urbanization, the object-oriented approach and SOA 121 8.5. Advantages of the Praxeme method 124 8.5.1. A method that unites different approaches and integrates SOA 124 8.5.2. Risks associated with the Praxeme method 126 Chapter 9. Modeling with Praxeme 129 9.1. The modeling of requirements 130 9.2. Semantic modeling 130 9.2.1. The basic principles 130 9.2.2. How to obtain a semantic model 133 9.2.3. How to validate a semantic model 134 9.2.4. Semantic models and property rights – who owns a semantic model? 134 9.2.5. The structure of a semantic model 135 9.3. Pragmatic modeling 137 9.3.1. The basic principles 137 9.3.2. A new procedure for designing processes 139 9.3.3. Usage view 140 9.4. Pre-modeling 142 9.5. Logical modeling 143 9.5.1. SOA’s style of logical architecture 143 9.5.2. Service-oriented architecture as logical architecture 144 9.5.3. Types of logical components 145 9.5.4. The strata of logical architecture 151 9.5.5. Pivot language 153 9.5.6. Service algorithm specification 154 9.5.7. Specification of the services’ pre- and post-conditions 154 9.5.8. Logical architecture of data 156 9.5.9. Logical architecture of data repositories 157 9.5.10. Logical architecture and user interface 158 9.5.11. Designing a logic for tests 159 9.5.12. Considering ERP 160 9.5.13. Considering existent assets 160 9.5.14. Federation of systems 160 9.5.15. Roles of logical modeling 161 9.6. Logical modeling of batch computing 162 9.7. Technical modeling 163 9.7.1. Required competences 163 9.7.2. Technical/logical negotiation 164 9.8. Software modeling 166 9.8.1. General principles 166 9.8.2. Towards the industrialization of programming 169 9.9. Benefits of the methodology 169 9.9.1. Opportunities 169 9.9.2. Obstacles 171 Part IV. Mastering Existing Techniques 173 Chapter 10. Tools for Industrializing the Method 175 10.1. Requirements in the industrialization of procedures 176 10.2. Frameworks and design patterns 178 10.2.1. From services framework to virtual machines 179 10.2.2. Frameworks and human–machine interfaces 182 10.2.3. Design patterns 186 10.3. Tools for increased agility 189 10.3.1. Rules engine 189 10.3.2. Reference data management system 196 10.4. Representation tools 203 10.4.1. Modeling CASE tool 203 10.4.2. Formal language (pseudo-language) 207 10.4.3. MDA 209 10.5. Tools for tests and management 212 10.5.1. Non-regression tests 212 10.5.2. Designing tests and test data 213 10.5.3. Different levels of tests 214 10.6. Tools for the management of different versions and the configuration of programs 216 10.6.1. The level of versions and variants 216 10.6.2. The level of delivery packages 218 10.7. Benefits of using tools in the method 219 10.7.1. Opportunities 219 10.7.2. Risks 220 Chapter 11. Systems Integration and Common Information Language 223 11.1. New requirements in communication 225 11.1.1. Increase of data flow 225 11.1.2. Considering the business 225 11.1.3. Take the bus! 227 11.2. ESB’s functions 227 11.2.1. Use perimeter 227 11.2.2. ESB’s components 230 11.3. Integrating ESB into SI 235 11.3.1. Towards a common language 235 11.4. ESB’s benefits 239 11.4.1. Opportunities 239 11.4.2. Limitations 240 Chapter 12. SOA Platform 243 12.1. Requirements for the global vision of technical architecture 244 12.2. New technical components 245 12.2.1. The transformation of data 245 12.2.2. From a directory to a registry of services 248 12.2.3. Security 250 12.2.4. Traceability of services in production 252 12.2.5. BAM and CEP 254 12.2.6. Business Intelligence 255 12.2.7. Editing 257 12.3. Managing performance 259 12.3.1. A new order of things? 259 12.3.2. Best practice 260 12.3.3. Testing performance 261 12.4. Managing exploitation 263 12.5. Managing maintenance 269 12.6. Benefits of SOA platforms 265 12.6.1. Opportunities 265 12.6.2. Limitations 266 Chapter 13. Rules Management at the Scale of the Whole Enterprise 267 Jérôme BOYER, ILOG Software 13.1. Overview 267 13.2. Deep view 268 13.3. When to use a rule engine 271 13.4. Logical architecture view 273 13.5. BRMS and SOA 283 Chapter 14. Semantic Integration 287 Erik STEINHOLTZ, Progress Software 14.1. Enabling the adaptive enterprise 288 14.2. Inhibitors for change 289 14.3. Definition of semantic integration 290 14.4. Parallel track information modeling 291 14.5. Change inhibitors addressed with semantic integration 294 14.6. Putting it to work 295 14.6.1. Canonicalizing the BIM 295 14.6.2. The quick win: a pilot project 296 14.6.3. Using the CIM for integration 296 14.6.4. Tools used 297 14.6.5. Managing change and keeping the models alive 298 Conclusion 299 Weblinks 303 Bibliography 305 Special Technical Note 307 Index 309

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Book SynopsisA major challenge in constraint programming is to develop efficient generic approaches to solve instances of the constraint satisfaction problem (CSP). With this aim in mind, this book provides an accessible synthesis of the author's research and work in this area, divided into four main topics: representation, inference, search, and learning. The results obtained and reproduced in this book have a wide applicability, regardless of the nature of the problem to be solved or the type of constraints involved, making it an extremely user-friendly resource for those involved in this field.Table of ContentsAcknowledgements 11 Notation 13 Main Acronyms 19 List of Algorithms 21 Introduction 27 Chapter 1. Constraint Networks 39 1.1 . Variables and constraints 39 1.2. Networks of variables and constraints . 51 1.2. Examples of constraint networks 65 1.4. Partial orders, decisions, nogoods and properties 74 1.5. Data structures to represent constraint networks 86 Chapter 2. Random and Structured Networks 93 2.1. Random constraint networks 94 2.2. Structured constraint networks 109 PART ONE. INFERENCE 133 Chapter 3. Consistencies 137 3.1. Basic consistencies 138 3.2. Stability of consistencies 143 3.3. Domain-filtering consistencies 150 3.4. Higher-order consistencies 162 3.5. Global consistency 173 3.6. Caveats about node, arc and path consistencies 184 Chapter 4. Generic GAC Algorithms 185 4.1.Coarse-grained propagation schemes 186 4.2. Iterating over valid tuples 97 4.3. GAC3 and GAC2001 200 4.4. More about general-purpose GAC algorithms 205 4.5. Improving the efficiency of generic GAC algorithms 214 4.6. Experimental results 233 4.7. Discussion 236 Chapter 5. Generalized Arc Consistency for Table Constraints 239 5.1. Classical schemes 240 5.2. Indexing-based approaches 244 5.3. Compression-based approaches 253 5.4. GAC-valid+allowed scheme 264 5.5. Simple tabular reduction 269 5.6. GACfor negative table constraints 279 5.7. Experimental results 283 5.8. Conclusion 286 Chapter 6. Singleton Arc Consistency 287 6.1. SAC1 and SAC2 289 6.2. SAC-Opt and SAC-SDS 290 6.3. SAC3 292 6.4. SAC3+ 296 6.5. Illustration 299 6.6. Weaker and stronger forms of SAC 300 6.7. Experimental results 313 6.8. Conclusion 316 Chapter 7. Path and Dual Consistency 319 7.1. Qualitative study 321 7.2. Enforcing (conservative) path consistency 331 7.3. Enforcing strong (conservative) dual consistency 336 7.4. Experimental results 348 7.5. Conclusion 353 PART TWO. SEARCH 355 Chapter 8. Backtrack Search 359 8.1. General description 361 8.2. Maintaining (generalized) arc consistency 367 8.3. Classical look-ahead and look-back schemes 370 8.4. Illustrations 378 8.5. The role of explanations 383 Chapter 9. Guiding Search toward Conflicts 391 9.1. Search-guiding heuristics 392 9.2. Adaptive heuristics 398 9.3. Strength of constraint weighting 405 9.4. Guiding search to culprit decisions 415 9.5. Conclusion 427 Chapter 10. Restarts and Nogood Recording 431 10.1. Restarting search 432 10.2. Nogood recording from restarts 436 10.3. Managing standard nogoods 441 10.4. Minimizing nogoods 450 10.5. Experimental results 454 10.6. Conclusion 457 Chapter 11. State-based Reasoning 459 11.1. Inconsistent partial states 460 11.2. Learning from explanations and failed values 470 11.3. Reducing elementary inconsistent partial states 476 11.4. Equivalence detection 487 11.5. Experimental results 492 11.6. Conclusion 494 Chapter 12. Symmetry Breaking 495 Christophe LECOUTRE, Sébastien TABARY 12.1. Group theory 496 12.2. Symmetries on constraint networks 499 12.3. Symmetry-breaking methods 503 12.4. Automatic symmetry detection 508 12.5. Lightweight detection of variable symmetries 511 12.6. A GAC algorithm for lexicographic ordering constraints 520 12.7. Experimental results 527 Appendices 531 Bibliography 547 Index 571

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Book SynopsisInformation systems have an enormous potential for improving business performance. With this in mind, companies must set out to exploit and optimize this potential without delay in order to improve their efficiency and continue to set themselves apart from the competition. This comprehensive text provides the information needed to understand and implement these systems at a practical level.Table of ContentsPreface xi Acknowledgements xv Chapter 1. Innovation for Business Value and Cost-killing 1 1.1. Supporting profit and growth 3 1.2. Assessing innovation 9 1.3. Agility and alignment 15 1.4. Sustainable development and information assets 24 Chapter 2. The Transverse Information System 29 2.1. A regular increase in power 30 2.2. Optimizing business unit assets 36 2.3. The impact on the IT department agenda 41 Chapter 3. Master Data 49 3.1. An unclaimed asset 50 3.2. Master data management: centralization 65 3.3. Enterprise information integration: federation 74 3.4. Between centralization and federation 78 3.5. Data governance 80 3.6. Towards information management 83 3.7. Bibliography 84 Chapter 4. Service-Oriented Architectures 85 4.1. Basic impacts 87 4.2. A major lever for a change in progress 93 4.3. A new experiment in the finance bank 102 4.4. Technologies and architecture 106 4.5. Flexibility is an event? Yes, agent! 118 Chapter 5. Business Process Management 121 5.1. From managing business processes to BPM 122 5.2. Understanding BPM 137 5.3. The business process from the IS perspective 147 5.4. BPM promises and prospects 155 5.5. Conclusion: the place of BPM in the company and in the IS 157 Chapter 6. Exchange Platforms 159 6.1. The development of data exchanges 159 6.2. Technologies and architectures 172 6.3. Project typology 185 6.4. A common foundation 188 Chapter 7. Complex, Innovative Business Architectures 189 7.1. Natural connections 190 7.2. An investigation into the distribution sector 198 7.3. A project in the energy sector 205 7.4. A program in retail banking 209 Chapter 8. The Impact of NISS on Software Implementation 219 8.1. The process standard 221 8.2. Towards assembly and beyond 225 8.3. Model-driven architecture and docking 241 8.4. A “sourcing” process to be defined 244 Chapter 9. From Implementation to Measurment 247 9.1. Towards operational excellence 248 9.2. Business activity monitoring 253 9.3. SOA management 269 9.4. The loop is completed 272 Chapter 10. Contribution and Impact of NISS on Organization 275 10.1. From the business unit to IT: a new fluency 276 10.2. Governance of information assets 283 10.3. Organization methods 297 10.4. Managing change and maturity stages 305 Chapter 11. How to Get the Best Out of NISS 307 11.1. The initial phases 307 11.2. The foundations: creating platforms 318 11.3. From the process angle 322 11.4. Here and now 328 11.5. Bibliography 329 Index 331

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Book SynopsisIn today’s digital environment, distributed systems are increasingly present in a wide variety of environments, ranging from public software applications to critical systems. Distributed Systems introduces the underlying concepts, the associated design techniques and the related security issues. Distributed Systems: Design and Algorithms, is dedicated to engineers, students, and anyone familiar with algorithms and programming, who want to know more about distributed systems. These systems are characterized by: several components with one or more threads, possibly running on different processors; asynchronous communications with possible additional assumptions (reliability, order preserving, etc.); local views for every component and no shared data between components. This title presents distributed systems from a point of view dedicated to their design and their main principles: the main algorithms are described and placed in their application context, i.e. consistency management and the way they are used in distributed file-systems.Table of ContentsForeword 9 Chapter 1. Introduction 13 Serge HADDAD, Fabrice KORDON, Laurent PAUTET and Laure PETRUCCI FIRST PART. LARGE SCALE PEER-TO-PEER DISTRIBUTED SYSTEMS 19 Chapter 2. Introduction to Large-Scale Peer-to-Peer Distributed Systems 21 Fabrice KORDON 2.1. “Large-Scale” distributed systems? 21 2.2. Consequences of “large-scale” 22 2.3. Some large-scale distributed systems 23 2.4. Architectures of large scale distributed systems 26 2.5. Objective of Part 1 30 2.6. Bibliography 31 Chapter 3. Design Principles of Large-Scale Distributed System 33 Xavier BONNAIRE and Pierre SENS 3.1. Introduction to peer-to-peer systems 33 3.2. The peer-to-peer paradigms 34 3.3. Services on structured overlays 41 3.4. Building trust in P2Psystems 43 3.5. Conclusion 52 3.6. Bibliography 53 Chapter 4. Peer-to-Peer Storage 59 Olivier MARIN, Sébastien MONNET and Gaël THOMAS 4.1. Introduction 59 4.2. BitTorrent 60 4.3. Gnutella 66 4.4. Conclusion 79 4.5. Bibliography 79 Chapter 5. Large-Scale Peer-to-Peer Game Applications 81 Sébastien MONNET and Gaël THOMAS 5.1. Introduction 81 5.2. Large-scale game applications: model and specific requirements 83 5.3. Overview of peer-to-peer overlays for large-scale game applications 90 5.4. Overlays for FPS games 93 5.5. Overlays for online life-simulation games 95 5.6. Conclusion 100 5.7. Bibliography 101 SECOND PART. DISTRIBUTED, EMBEDDED AND REAL-TIME SYSTEMS 105 Chapter 6. Introduction to Distributed Embedded and Real-time Systems 107 Laurent PAUTET 6.1. Distributed real-time embedded systems 108 6.2. Safety critical systems as examples of DRE systems 109 6.3. Design process of DRE systems 112 6.4. Objectives of Part 2 114 6.5. Bibliography 115 Chapter 7. Scheduling in Distributed Real-Time Systems 117 Emmanuel GROLLEAU, Michaël RICHARD, and Pascal RICHARD 7.1. Introduction 117 7.2. Generalities about real-time systems 118 7.3. Temporal correctness 122 7.4. WCRT of the tasks 126 7.5. WCRT of the messages 142 7.6. Case study 149 7.7. Conclusion 154 7.8. Bibliography 155 Chapter 8. Software Engineering for Adaptative Embedded Systems 159 Etienne BORDE 8.1. Introduction 159 8.2. Adaptation, an additional complexity factor 160 8.3. Theoretical aspects of adaptation management 163 8.4. Technical solutions for the design of adaptative embedded systems 171 8.5. An example of adaptative system from the robotic domain 176 8.6. Applying MDE techniques to the design of the robotic use-case 177 8.7. Exploitation of the models 184 8.8. Conclusion 188 8.9. Bibliography 189 Chapter 9. The Design of Aerospace Systems 191 Maxime PERROTIN, Julien DELANGE, and Jérôme HUGUES 9.1. Introduction 191 9.2. Flight software typical architecture 193 9.3. Traditional development methods and their limits 195 9.4. Modeling a software system using TASTE: philosophy 197 9.5. Common solutions 199 9.6. What TASTE specifically proposes 200 9.7. Modeling process and tools 201 9.8. Technology 208 9.9. Model transformations 209 9.10. The TASTE run-time 213 9.11. Illustrating our process by designing heterogeneous systems 215 9.12. First user feedback and TASTE future 224 9.13. Conclusion 225 9.14. Bibliography 226 THIRD PART. SECURITY IN DISTRIBUTED SYSTEMS 229 Chapter 10. Introduction to Security Issues in Distributed Systems 231 Laure PETRUCCI 10.1. Problem 231 10.2. Secure data exchange 233 10.3. Security in specific distributed systems 234 10.4. Outline of art III 234 10.5. Bibliography 235 Chapter 11. Practical Security in Distributed Systems 237 Benoît BERTHOLON, Christophe CÉRIN, Camille COTI, and Sébastien VARRETTE, Jean-Christophe DUBACQ 11.1. Introduction 237 11.2. Confidentiality 249 11.3. Authentication 252 11.4. Availability and fault tolerance 261 11.5. Ensuring resource security 278 11.6. Result checking in distributed computations 283 11.7. Conclusion 291 11.8. Bibliography 292 Chapter 12. Enforcing Security with Cryptography 301 Sami HARARI and Laurent POINSOT 12.1. Introduction 301 12.2. Cryptography: from a general perspective 303 12.3. Symmetric encryption schemes 308 12.4. Prime numbers and public key cryptography 324 12.5. Conclusion 328 12.6. Bibliography 329 Index 333

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Book SynopsisStarting with an updated description of Allen's calculus, the book proceeds with a description of the main qualitative calculi which have been developed over the last two decades. It describes the connection of complexity issues to geometric properties. Models of the formalisms are described using the algebraic notion of weak representations of the associated algebras. The book also includes a presentation of fuzzy extensions of qualitative calculi, and a description of the study of complexity in terms of clones of operations.Table of ContentsIntroduction. Qualitative Reasoning xvii Chapter 1. Allen’s Calculus 1 1.1. Introduction 1 1.2. Allen’s interval relations 6 1.3. Constraint networks 8 1.4. Constraint propagation 17 1.5. Consistency tests 26 Chapter 2. Polynomial Subclasses of Allen’s Algebra 29 2.1. “Show me a tractable relation!” 29 2.2. Subclasses of Allen’s algebra 30 2.3. Maximal tractable subclasses of Allen’s algebra 52 2.4. Using polynomial subclasses 57 2.5. Models of Allen’s language 60 2.6. Historical note 61 Chapter 3. Generalized Intervals 63 3.1. “When they built the bridge . “ 63 3.2. Entities and relations 65 3.3. The lattice of basic (p, q)-relations 68 3.4. Regions associated with basic (p, q)-relations 69 3.5. Inversion and composition 73 3.6. Subclasses of relations: convex and pre-convex relations 79 3.7. Constraint networks 82 3.8. Tractability of strongly pre-convex relations 83 3.9. Conclusions 84 3.10. Historical note 85 Chapter 4. Binary Qualitative Formalisms 87 4.1. “Night driving” 87 4.2. Directed points in dimension 1 92 4.3. Directed intervals 97 4.4. The OPRA direction calculi 99 4.5. Dipole calculi 100 4.6. The Cardinal direction calculus 101 4.7. The Rectangle calculus 104 4.8. The n-point calculus 106 4.9. The n-block calculus 108 4.10. Cardinal directions between regions 109 4.11. The INDU calculus 123 4.12. The 2n-star calculi 126 4.13. The Cyclic interval calculus 128 4.14. The RCC–8 formalism 131 4.15. A discrete RCC theory 137 Chapter 5. Qualitative Formalisms of Arity Greater than 2 145 5.1. “The sushi bar” 145 5.2. Ternary spatial and temporal formalisms 146 5.3. Alignment relations between regions 155 5.4. Conclusions 158 Chapter 6. Quantitative Formalisms, Hybrids, and Granularity 159 6.1. “Did John meet Fred this morning?”159 6.2. TCSP metric networks 160 6.3. Hybrid networks 164 6.4. Meiri’s formalism 168 6.5. Disjunctive linear relations (DLR) 174 6.6. Generalized temporal networks 175 6.7. Networks with granularity 179 Chapter 7. Fuzzy Reasoning 187 7.1. “Picasso’s Blue period” 187 7.2. Fuzzy relations between classical intervals 188 7.3. Events and fuzzy intervals 195 7.4. Fuzzy spatial reasoning: a fuzzy RCC 208 7.5. Historical note 222 Chapter 8. The Geometrical Approach and Conceptual Spaces 223 8.1. “What color is the chameleon?” 223 8.2. Qualitative semantics 224 8.3. Why introduce topology and geometry? 225 8.4. Conceptual spaces 226 8.5. Polynomial relations of INDU 237 8.6. Historical note 258 Chapter 9. Weak Representations 259 9.1. “Find the hidden similarity” 259 9.2. Weak representations 261 9.3. Classifying the weak representations of An 275 9.4. Extension to the calculi based on linear orders 283 9.5. Weak representations and configurations 290 9.6. Historical note 304 Chapter 10. Models of RCC−8 305 10.1. “Disks in the plane” 305 10.2. Models of a composition table 307 10.3. The RCC theory and its models 312 10.4. Extensional entries of the composition table 319 10.5. The generalized RCC theory 329 10.6. A countable connection algebra 337 10.7. Conclusions 341 Chapter 11. A Categorical Approach of Qualitative Reasoning 343 11.1. “Waiting in line” 343 11.2. A general construction of qualitative formalisms 346 11.3. Examples of partition schemes 349 11.4. Algebras associated with qualitative formalisms 350 11.5. Partition schemes and weak representations 352 11.6. A general definition of qualitative formalisms 353 11.7. Interpretating consistency 355 11.8. The category of weak representations 357 11.9. Conclusions 360 Chapter 12. Complexity of Constraint Languages 363 12.1. “Sudoku puzzles” 363 12.2. Structure of the chapter 365 12.3. Constraint languages 366 12.4. An algebraic approach of complexity 367 12.5. CSPs and morphisms of relational structures 368 12.6. Clones of operations 373 12.7. From local consistency to global consistency 375 12.8. The infinite case 376 12.9. Disjunctive constraints and refinements 382 12.10. Refinements and independence 389 12.11. Historical note 390 Chapter 13. Spatial Reasoning and Modal Logic 391 13.1. “The blind men and the elephant” 391 13.2. Space and modal logics 393 13.3. The modal logic S4 393 13.4. Topological models 396 13.5. Translating the RCC−8 predicates 408 13.6. An alternative modal translation of RCC−8 409 13.7. Generalized frames 410 13.8. Complexity 411 13.9. Complements 412 Chapter 14. Applications and Software Tools 413 14.1. Applications 413 14.2. Software tools 416 Chapter 15. Conclusion and Prospects 423 15.1. Introduction 423 15.2. Combining qualitative formalisms 423 15.3. Spatio-temporal reasoning 426 15.4. Alternatives to qualitative reasoning 430 15.5. To conclude — for good 434 Appendix A. Elements of Topology 435 A.1. Topological spaces 435 A.2. Metric spaces 445 A.3. Connectedness and convexity 447 Appendix B. Elements of Universal Algebra 451 B.1. Abstract algebras 451 B.2. Boolean algebras 452 B.3. Binary relations and relation algebras 454 B.4. Basic elements of the language of categories 457 Appendix C. Disjunctive Linear Relations 463 C.1. DLRs: definitions and satisfiability 463 C.2. Linear programming 464 C.3. Complexity of the satisfiability problem 466 Bibliography 471 Index 501

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Book SynopsisWithin the framework of the Sixth I-ESA International Conference, supported by the INTEROP VLab (International Virtual Laboratory on Enterprise Interoperability, http://www.interop-vlab.eu), three workshops and a Doctoral Symposium have been organized in order to strengthen some key topics related to interoperability for enterprise applications and software. The workshops were selected to complement the conference topics, leaving more time to researchers for brainstorming and then coming up, at the end of the workshops, with new research directions for the future. The goal of the workshop “Standards – a Foundation for Interoperability” is to increase awareness and understanding of interoperability standards as a fundamental need. The workshop “Use of MDI/SOA Concepts in Industry” promotes the application of MDI (Model-Driven Interoperability) combined with SOA (Services Oriented Architecture) and the associated technology (BPM, Enterprise Modeling, ontology, mediation, model transformation, etc.) in industry. The workshop on “Dynamic Management across Interoperating Enterprises” investigates the need for enhancements to current business management systems and processes to address the needs of global trading across enterprises utilizing the new service-oriented Internet. Finally, the Doctoral Symposium has given the opportunity for students involved in the preparation of their PhDs in this emerging area to present and discuss their research issues and ideas with senior researchers.Table of ContentsEditorial Hervé Panetto, Nacer Boudjlida xi Session 1. Standards – A Foundation for Interoperability 1 Standards Workshop Chairs’ Message Martin Zelm, David Chen 5 Standards for Enterprise Interoperation – How to Improve? Martin Zelm, Kurt Kosanke 7 Framework for Enterprise Interoperability and Maturity Model (CEN/ISO 11354) David Chen 15 Testing Interoperability Standards – A Test Case Generation Methodology Nenad Ivezic, Jungyub Woo 23 OMG Specifications for Enterprise Interoperability Brian Elvesæter, Arne-Jørgen Berre 31 Standards Creation and Adoption for SME Networks Piero De Sabbata, Nicola Gessa, Arianna Brutti, Cristiano Novelli, Angelo Frascella, Gianluca D’Agosta 41 The European Public Procurement Initiative and Standards for Information Exchange Tim McGrath 53 Challenges in Project Management Georgios Kapogiannis, Colin Piddington 61 Session 2. Use of MDI/SOA Concepts in Industry 67 MDI/SOA Workshop Chairs’ Message Guy Doumeingts, Martine Grandin-Dubost 71 Application of SHAPE Technologies in Production and Process Optimization Brian Elvesæter, Arne-Jørgen Berre, Einar Landre 73 An Exploration of Foundation Ontologies and Verification Methods for Manufacturing Knowledge Sharing R. Young, N. Chungoora, Z. Usman, N. Anjum, G. Gunendran, C. Palmer, J.A. Harding, K. Case, A.-F. Cutting-Decelle 83 ISTA3 Methodology Application Case Nabila Zouggar, Mickaël Romain, Guy Doumeingts, Sébastien Cazajous, Yves Ducq, Christophe Merlo, Martine Grandin-Dubost 95 Session 3. Doctoral Symposium 111 Doctoral Symposium Chair’s Message Jenny A. Harding 115 The Mediation Information System Engineering Project: Status and Perspectives N. Boissel-Dallier, F. Bénaben, H. Pingaud, J.-P. Lorré 117 Quality Measurement of Semantic Standards E.J.A. Folmer, P.H.W.M. Oude Luttighuis, J. van Hillegersberg 125 Towards a Model-Driven and Role-Configurable Methodology Suite for Enterprise and Service-Oriented Interoperability Brian Elvesæter, Arne-Jørgen Berre 133 Mediation Information System Engineering: Business and Logic Characterization in a Collaborative Situation W. Mu, F. Bénaben, H. Pingaud 139 Role of Semantic Web in the Changing Context of Enterprise Collaboration N. Khilwani, J. A. Harding 147 A Dynamic Knowledge Management Framework B. A. Piorkowski, J. X. Gao 155 Author Index 163

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Book SynopsisCombining multiple sensors in order to better grasp a tricky, or even critical, situation is an innate human reflex. Indeed, humans became aware, very early on, of the need to combine several of our senses so as to acquire a better understanding of our surroundings when major issues are at stake. On the basis of this need, we have naturally sought to equip ourselves with various kinds of artificial sensors to enhance our perceptive faculties. The association of multiple heterogeneous sensors provides a reliable and efficient situation assessment in difficult operational contexts, but imperfect local observations need to be managed in a suitable way (uncertainty, imprecision, incompleteness, unreliability, etc.). The theories of uncertainty make it possible to benefit from such information, but the implementation of these theories requires specific developments to meet the needs of multisensor data fusion. This book first discusses basic questions such as: Why and when is multiple sensor fusion necessary? How can the available measurements be characterized in such a case? What is the purpose and the specificity of information fusion processing in multiple sensor systems? Considering the different uncertainty formalisms (probability, fuzzy set theory, possibility theory, belief function theory), a set of coherent operators corresponding to the different steps of a complete fusion process is then developed, in order to meet the requirements identified in the first part of the book. Furthermore, the implementation of these operators is illustrated and discussed within the framework of generic applications.Table of ContentsINTRODUCTION ix CHAPTER 1. MULTISENSOR DATA FUSION 1 1.1. Issues at stake 1 1.2. Problems 4 1.2.1. Interpretation and modeling of data 8 1.2.2. Reliability handling 10 1.2.3. Knowledge propagation 11 1.2.4. Matching of ambiguous data 12 1.2.5. Combination of sources14 1.2.6. Decision-making 16 1.3. Solutions 21 1.3.1. Panorama of useful theories 21 1.3.2. Process architectures 24 1.4. Position of multisensor data fusion 27 1.4.1. Peculiarities of the problem 27 1.4.2. Applications of multisensor data fusion 28 CHAPTER 2. REFERENCE FORMALISMS 31 2.1. Probabilities 31 2.2. Fuzzy sets 35 2.3. Possibility theory 39 2.4. Belief functions theory 43 2.4.1. Basic functions 44 2.4.2. A few particularly useful cases 47 2.4.3. Conditioning/deconditioning 49 2.4.4. Refinement/coarsening 50 CHAPTER 3. SET MANAGEMENT AND INFORMATION PROPAGATION 53 3.1. Fuzzy sets: propagation of imprecision 53 3.2. Probabilities and possibilities: the same approach to uncertainty 56 3.3. Belief functions: an overarching vision in terms of propagation 57 3.3.1. A generic operator: extension 58 3.3.2. Elaboration of a mass function with minimum specificity 61 3.3.3. Direct exploitation of the operator of extension 64 3.4. Example of application: updating of knowledge over time 66 CHAPTER 4. MANAGING THE RELIABILITY OF INFORMATION 71 4.1. Possibilistic view 72 4.2. Discounting of belief functions 73 4.3. Integrated processing of reliability 75 4.4. Management of domains of validity of the sources 77 4.5. Application to fusion of pixels from multispectral images 82 4.6. Formulation for problems of estimation 87 CHAPTER 5. COMBINATION OF SOURCES 91 5.1. Probabilities: a turnkey solution, Bayesian inference 92 5.2. Fuzzy sets: a grasp of axiomatics 94 5.3. Possibility theory: a simple approach to the basic principles 102 5.4. Theory of belief functions: conventional approaches 106 5.5. General approach to combination: any sets and logics 113 5.6. Conflict management 118 5.7. Back to Zadeh’s paradox 122 CHAPTER 6. DATA MODELING 127 6.1. Characterization of signals 127 6.2. Probabilities: immediate taking into account 130 6.3. Belief functions: an open-ended and overarching framework 131 6.3.1. Integration of data into the fusion process 132 6.3.2. Generic problem: modeling of Cij values 135 6.3.3. Modeling measurements with stochastic learning 139 6.3.4. Modeling measurements with fuzzy learning 144 6.3.5. Overview of models for belief functions 148 6.4. Possibilities: a similar approach 153 6.5. Application to a didactic example of classification 157 CHAPTER 7. CLASSIFICATION: DECISION-MAKING AND EXPLOITATION OF THE DIVERSITY OF INFORMATION SOURCES 165 7.1. Decision-making: choice of the most likely hypothesis 166 7.2. Decision-making: determination of the most likely set of hypotheses 168 7.3. Behavior of the decision operator: some practical examples 171 7.4. Exploitation of the diversity of information sources: integration of binary comparisons 175 7.5. Exploitation of the diversity of information sources: classification on the basis of distinct but overlapping sets 179 7.6. Exploitation of the diversity of the attributes: example of application to the fusion of airborne image data 189 CHAPTER 8. SPATIAL DIMENSION: DATA ASSOCIATION 193 8.1. Data association: a multiform problem, which is unavoidable in multisensor data fusion 194 8.2. Construction of a general method for data association 197 8.3. Simple example of the implementation of the method 203 CHAPTER 9. TEMPORAL DIMENSION: TRACKING 211 9.1. Tracking: exploitation of the benefits of multisensory data fusion 211 9.2. Expression of the Bayesian filter 218 9.2.1. Statistical gating 218 9.2.2. Updating 219 9.2.3. Prediction 220 9.3. Signal discrimination process 221 9.3.1. Fusion at the level of each resolution cell 222 9.3.2. Fusion at the level of the validation gate 224 9.3.3. Overview of a practical implementation of the discrimination method 226 9.4. Extensions of the basic MSF 228 9.4.1. Data association 228 9.4.2. Joint tracking of multiple targets 229 9.4.3. Multi-model filtering 231 9.5. Examples of application 232 9.5.1. Extraction power 233 9.5.2. Handling of unfamiliar signatures 235 9.5.3. Tracking on spatially ambiguous observations 238 CONCLUSION 241 BIBLIOGRAPHY 249 INDEX 257

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