Networks are now embedded in daily life thanks to smaller, faster, inexpensive components that are more powerful and increasingly connected. Parallel to this quantitative explosion of communication networks, technology has become more complex. This development comes with challenges related to management and control, and it has become necessary to manage the service level demands of the client to which the service provider commits. Different approaches to managing one or more service level components in different emerging environments are explored, such as: the Internet of Things, the Cloud, smart grids, e-health, mesh networking, D2D (Device to Device), smart cities and even green networking. This book therefore allows for a better understanding of the important challenges and issues relating to Quality of Service (QoS) management, security and mobility in these types of environment.

Table of Contents:
Preface xi Chapter 1. Service Level Management in the Internet of Things (IoT) 1 Ahmad KHALIL, Nader MBAREK and Olivier TOGNI 1.1. Introduction 1 1.2. IoT: definitions 2 1.3. IoT: an overview 3 1.3.1. IoT architectures 3 1.3.2. Application fields of the IoT 6 1.4. Security management and privacy protection in the IoT 8 1.4.1. Motivations and challenges 8 1.4.2. Security services in the IoT environment 10 1.4.3. Privacy protection and trust in the IoT 18 1.5. QoS management for IoT services 21 1.5.1. Motivations and challenges 21 1.5.2. Guaranteeing QoS in IoT 22 1.6. QBAIoT: QoS-based access method for IoT environments 28 1.6.1. Service level guarantee in the IoT 28 1.6.2. The QBAIoT process in the IoT 31 1.6.3. QBAIoT performance evaluation 36 1.7. Conclusion 38 1.8. References 39 Chapter 2. Service Level Management in the Cloud 45 Nader MBAREK 2.1. Introduction 45 2.2. The Cloud environment 46 2.2.1. Cloud Computing 46 2.2.2. Cloud Networking 50 2.2.3. Inter-Cloud 52 2.3. Service level and self-management in the Cloud 54 2.3.1. Quality of Service in a Cloud environment 54 2.3.2. Security in a Cloud environment 57 2.3.3. Self-management of Cloud environments 60 2.4. QoS guarantee in Cloud Networking 63 2.4.1. Cloud Networking architectures 63 2.4.2. Performance evaluation 68 2.5. Conclusion 75 2.6. References 75 Chapter 3. Managing Energy Demand as a Service in a Smart Grid Environment 83 Samira CHOUIKHI, Leila MERGHEM-BOULAHIA and Moez ESSEGHIR 3.1. Introduction 83 3.2. The Smart Grid environment 84 3.2.1. Smart microgrids 85 3.2.2. Information and communication infrastructure 86 3.3. Demand management: fundamental concepts 87 3.3.1. Predicting loads 87 3.3.2. DR – demand response 88 3.4. Demand-side management 89 3.4.1. The architectures and components of DSM platforms 90 3.4.2. Classifying DSM approaches 91 3.4.3. Deterministic approaches for individual users 92 3.4.4. Stochastic approaches for individual users 93 3.4.5. Deterministic approaches for consumer communities 94 3.4.6. Stochastic approaches for consumer communities 94 3.5. Techniques and methods for demand scheduling 96 3.5.1. Game theory 97 3.5.2. Multiagent systems 98 3.5.3. Machine learning 99 3.6. Conclusion 100 3.7. References 101 Chapter 4. Managing Quality of Service and Security in an e-Health Environment 107 Mohamed-Aymen CHALOUF 4.1. Introduction 107 4.2. e-health systems 109 4.2.1. Architecture 110 4.2.2. Characteristics 111 4.3. QoS in e-health systems 114 4.3.1. e-health services and QoS 114 4.3.2. QoS management in e-health systems 117 4.4. Security of e-health systems 124 4.4.1. Threats and attacks specific to e-health systems 124 4.4.2. Security management in e-health systems 127 4.5. Conclusion 130 4.6. References 131 Chapter 5. Quality of Service Management in Wireless Mesh Networks 139 Hajer BARGAOUI, Nader MBAREK and Olivier TOGNI 5.1. Introduction 139 5.2. WMNs: an overview 140 5.2.1. Definition of a WMN 140 5.2.2. Architecture of a radio mesh wireless network 140 5.2.3. Characteristics of a WMN environment 142 5.2.4. Standards for WMNs 143 5.2.5. Domains of applications 144 5.3. QoS in WMNs 146 5.3.1. QoS in networks 146 5.3.2. QoS constraints in WMNs 146 5.3.3. QoS mechanisms in WMNs 147 5.3.4. Research projects on QoS in WMNs 150 5.4. QoS-based routing for WMNs 152 5.4.1. Routing requirements in WMNs 152 5.4.2. Routing metrics in WMNs 153 5.4.3. QoS-based routing protocols in WMNs 154 5.5. HQMR: QoS-based hybrid routing protocol for mesh radio networks 157 5.5.1. Description of the HQMR protocol 157 5.5.2. How the HQMR protocol works 160 5.5.3. Validation of the HQMR protocol 162 5.6. Conclusion 168 5.7. References 168 Chapter 6. Blockchain Based Authentication and Trust Management in Decentralized Networks 175 Axel MOINET and Benoît DARTIES 6.1. Introduction 175 6.1.1. Challenges and motivations, the state of the art 177 6.1.2. Blockchain, a support for authentication and trust 181 6.2. The Blockchain Authentication and Trust Module (BATM) architecture 184 6.2.1. Context and development 184 6.2.2. Managing identities and authentication 185 6.2.3. Calculating trust and reputation using the MLTE algorithm 188 6.3. Evaluating BATM 197 6.3.1. Simulation plan 197 6.3.2. Results and interpretation 198 6.4. Conclusion 201 6.5. References 202 Chapter 7. How Machine Learning Can Help Resolve Mobility Constraints in D2D Communications 205 Chérifa BOUCETTA, Hassine MOUNGLA and Hossam AFIFI 7.1. Introduction 205 7.2. D2D communication and the evolution of networks 207 7.2.1. The discovery phase in D2D communications 208 7.2.2. The data exchange phase in D2D communications 209 7.2.3. Investigations into future mobile networks 210 7.3. The context for machine learning and deep learning 210 7.3.1. Overview of deep learning and its application 212 7.3.2. Types of machine learning 213 7.3.3. Linear regression and classification 213 7.4. Dynamic discovery 215 7.4.1. Real-time prediction of user density 216 7.4.2. The dynamic discovery algorithm 217 7.5. Experimental results 218 7.5.1. General hypotheses 218 7.5.2. Traffic with low user density 219 7.5.3. Traffic with high user density 219 7.6. Conclusion 222 7.7. References 222 Chapter 8. The Impact of Cognitive Radio on Green Networking: The Learning-through-reinforcement Approach 227 Mohammed Salih BENDELLA and Badr BENMAMMAR 8.1. Introduction 227 8.2. Green networking 228 8.2.1. Why should we reduce energy consumption? 228 8.2.2. Where can we reduce energy consumption? 228 8.2.3. Definition and objectives of green networking 229 8.3. Green strategies 230 8.3.1. Consolidation of resources 230 8.3.2. Selective connectivity 231 8.3.3. Virtualization 231 8.3.4. Energy-proportional computing 231 8.4. Green wireless networks 233 8.4.1. Energy efficiency in wireless networks 235 8.4.2. Controlling transmission power 236 8.5. How CR contributes to green networking 238 8.5.1. The principle behind CR 238 8.5.2. The cognition cycle 238 8.5.3. Green networking in CR networks 240 8.6. Learning through reinforcement by taking into account energy efficiency during opportunistic access to the spectrum 243 8.6.1. Formulating the problem 245 8.6.2. Comparison between CR and Q_learning enabled CR 247 8.7. Conclusion 248 8.8. References 249 List of Authors 253 Index 255