This book examines the invariants that unify networks in their diversity, as well as the specificities that differentiate them. It provides a reading grid that distinguishes a generic level where these systems find a common interpretation, and a specific level where appropriate analytical methods are used. Three case studies from different fields are presented to illustrate the purpose of the book in detail.
Table of Contents
Foreword ix
Introduction xi
Part 1. Network Variety and Modeling 1
Chapter 1. Network Typology 3
1.1. Introduction 3
1.1.1. Network description levels 3
1.1.2. Network, graph and flow 4
1.1.3. Shared or dedicated infrastructure 5
1.1.4. User inclusion 6
1.2. The principal networks 6
1.2.1. (Human) transport networks 6
1.2.2. (Goods) distribution and collection networks 7
1.2.3. Dedicated distribution and collection networks (of fluids and energy) 8
1.2.4. IT networks 9
1.2.5. Communication networks 9
1.2.6. Social and digital social networks 10
1.3. Characterization and typology of networks 11
1.3.1. Key characteristics 11
1.3.2. Network integration 12
1.3.3. Typology 13
1.4. Engineering issues 16
1.5. Performance indicators, evaluation, optimization 18
1.5.1. Performance indicators 18
1.5.2. Evaluation and optimization 20
1.6. Conclusion 23
Chapter 2. Modeling Discrete Flow Networks 25
2.1. Introduction 25
2.2. Structure 28
2.3. Characterization of a discrete flow 30
2.3.1. Statistical description 30
2.3.2. Probabilistic description 32
2.4. Activities 32
2.5. Control system 37
2.6. Resources 40
2.7. Fluid kinematics 41
2.7.1. Flow/resource/decision synchronization 42
2.7.2. Congestion phenomenon 48
2.7.3. Dissemination of information in social networks 51
2.8. Formalisms for modeling flows in a network 52
2.8.1. BPM tools 53
2.8.2. Timed Petri nets 53
2.8.3. Flow networks 54
2.8.4. Queuing networks 55
2.9. Multi-modeling 57
2.9.1. Multi-formalism versus mono-formalism 57
2.9.2. The DEVS hierarchical model 60
2.9.3. Multi-layer networks 62
2.10. Conclusion 64
Part 2. Network Analysis Methods and Applications 67
Chapter 3. Exact Methods Applied to the Flow Analysis of Topological Networks 69
3.1. Introduction 69
3.2. Additive flow networks - deterministic modelling by flow networks 71
3.2.1. Two-terminal series-parallel graph 72
3.2.2. General case - max-flow/min-cut 74
3.3. Additive flow networks - stochastic modelling by queuing networks 76
3.4. Synchronized flow networks - modeling by timed event graphs 81
3.4.1. Steady-state analysis of timed event graphs 81
3.4.2. Example of application: sizing a flow-shop 83
3.5. Conclusion 88
Chapter 4. Simulation Techniques Applied to the Analysis of Sociological Networks 91
4.1. Introduction 91
4.2. Simulation techniques 92
4.2.1. Discrete event simulation (worldviews) 94
4.2.2. DEVS formalism 96
4.2.3. Coupling simulation/resolutive methods 100
4.2.4. Distributed simulation 102
4.2.5. Architectural solutions 103
4.2.6. Time management and synchronization 104
4.2.7. Pessimistic approach 104
4.2.8. Optimistic approach 105
4.2.9. HLA 106
4.2.10. Cosimulation 107
4.2.11. FMI/FMU 108
4.2.12. FMI/FMU and HLA coupling 109
4.3. Simulation of flows in sociological networks 110
4.3.1. Behavioral simulation based on DEVS formalism 111
4.3.2. Application study 113
4.4. Conclusion 116
Part 3. Case Studies 119
Chapter 5. Smart Grid 121
5.1. Summary of the study 122
5.2. Demand profile 122
5.3. Solar power station, fuel station and regional import 123
5.4. Hydroelectric power station and PHES 123
5.5. Operational issues 124
5.6. Model 125
5.6.1. Decision variables 125
5.6.2. Constraints 126
5.6.3. Objective function 127
5.7. Optimization results 128
Chapter 6. Forestry Logistics 131
6.1. Summary of the study 132
6.2. Forest timber supply problem 132
6.3. Tactical planning model 134
6.4. Logistics benchmarking 136
6.4.1. AS IS scenario (non-collaborative logistics) 136
6.4.2. TO BE scenario (collaborative logistics) 137
6.4.3. Results 138
6.5. Conclusion 139
Chapter 7. Multi-layered Digital Social Networks 143
7.1. Summary of the study 144
7.2. Digital social networks 144
7.3. Studying digital social networks via an interview broadcast 145
7.3.1. Pre-interview social network scenario 146
7.3.2. Social network audience 148
7.4. Modeling and simulation 148
7.4.1. Modeling the interview production and broadcast processes 148
7.4.2. MSN/HLA simulation architecture 149
7.5. Simulation results 152
7.6. Conclusion and perspectives 154
References 157
Index 167
