Service level management in emerging environments / / edited by Nader Mbarek

• Pubblicazione: London, England ; ; Hoboken, New Jersey : , : ISTE Ltd. : , : John Wiley & Sons, Incorporated, , [2020]; ©2020
• Descrizione fisica: 1 online resource (276 pages) : illustrations
• Disciplina: 004.6
• Soggetto topico: Internet of things - Management; Computer networks - Management; Cloud computing - Management
• Persona (resp. second.): MbarekNader
• Nota di contenuto: Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Preface -- 1 Service Level Management in the Internet of Things (IoT) -- 1.1. Introduction -- 1.2. IoT: definitions -- 1.3. IoT: an overview -- 1.3.1. IoT architectures -- 1.3.2. Application fields of the IoT -- 1.4. Security management and privacy protection in the IoT -- 1.4.1. Motivations and challenges -- 1.4.2. Security services in the IoT environment -- 1.4.3. Privacy protection and trust in the IoT -- 1.5. QoS management for IoT services -- 1.5.1. Motivations and challenges -- 1.5.2. Guaranteeing QoS in IoT -- 1.6. QBAIoT: QoS-based access method for IoT environments -- 1.6.1. Service level guarantee in the IoT -- 1.6.2. The QBAIoT process in the IoT -- 1.6.3. QBAIoT performance evaluation -- 1.7. Conclusion -- 1.8. References -- 2 Service Level Management in the Cloud -- 2.1. Introduction -- 2.2. The Cloud environment -- 2.2.1. Cloud Computing -- 2.2.2. Cloud Networking -- 2.2.3. Inter-Cloud -- 2.3. Service level and self-management in the Cloud -- 2.3.1. Quality of Service in a Cloud environment -- 2.3.2. Security in a Cloud environment -- 2.3.3. Self-management of Cloud environments -- 2.4. QoS guarantee in Cloud Networking -- 2.4.1. Cloud Networking architectures -- 2.4.2. Performance evaluation -- 2.5. Conclusion -- 2.6. References -- 3 Managing Energy Demand as a Service in a Smart Grid Environment -- 3.1. Introduction -- 3.2. The Smart Grid environment -- 3.2.1. Smart microgrids -- 3.2.2. Information and communication infrastructure -- 3.3. Demand management: fundamental concepts -- 3.3.1. Predicting loads -- 3.3.2. DR - demand response -- 3.4. Demand-side management -- 3.4.1. The architectures and components of DSM platforms -- 3.4.2. Classifying DSM approaches -- 3.4.3. Deterministic approaches for individual users. ; 3.4.4. Stochastic approaches for individual users -- 3.4.5. Deterministic approaches for consumer communities -- 3.4.6. Stochastic approaches for consumer communities -- 3.5. Techniques and methods for demand scheduling -- 3.5.1. Game theory -- 3.5.2. Multiagent systems -- 3.5.3. Machine learning -- 3.6. Conclusion -- 3.7. References -- 4 Managing Quality of Service and Security in an e-Health Environment -- 4.1. Introduction -- 4.2. e-health systems -- 4.2.1. Architecture -- 4.2.2. Characteristics -- 4.3. QoS in e-health systems -- 4.3.1. e-health services and QoS -- 4.3.2. QoS management in e-health systems -- 4.4. Security of e-health systems -- 4.4.1. Threats and attacks specific to e-health systems -- 4.4.2. Security management in e-health systems -- 4.5. Conclusion -- 4.6. References -- 5 Quality of Service Management in Wireless Mesh Networks -- 5.1. Introduction -- 5.2. WMNs: an overview -- 5.2.1. Definition of a WMN -- 5.2.2. Architecture of a radio mesh wireless network -- 5.2.3. Characteristics of a WMN environment -- 5.2.4. Standards for WMNs -- 5.2.5. Domains of applications -- 5.3. QoS in WMNs -- 5.3.1. QoS in networks -- 5.3.2. QoS constraints in WMNs -- 5.3.3. QoS mechanisms in WMNs -- 5.3.4. Research projects on QoS in WMNs -- 5.4. QoS-based routing for WMNs -- 5.4.1. Routing requirements in WMNs -- 5.4.2. Routing metrics in WMNs -- 5.4.3. QoS-based routing protocols in WMNs -- 5.5. HQMR: QoS-based hybrid routing protocol for mesh radio networks -- 5.5.1. Description of the HQMR protocol -- 5.5.2. How the HQMR protocol works -- 5.5.3. Validation of the HQMR protocol -- 5.6. Conclusion -- 5.7. References -- 6 Blockchain Based Authentication and Trust Management in Decentralized Networks -- 6.1. Introduction -- 6.1.1. Challenges and motivations, the state of the art -- 6.1.2. Blockchain, a support for authentication and trust. ; 6.2. The Blockchain Authentication and Trust Module (BATM)architecture -- 6.2.1. Context and developmentBATM architecture was proposed as -- 6.2.2. Managing identities and authentication -- 6.2.3. Calculating trust and reputation using the MLTE algorithm -- 6.3. Evaluating BATM -- 6.3.1. Simulation plan -- 6.3.2. Results and interpretation -- 6.4. Conclusion -- 6.5. References -- 7 How Machine Learning Can Help Resolve Mobility Constraints in D2D Communications -- 7.1. Introduction -- 7.2. D2D communication and the evolution of networks -- 7.2.1. The discovery phase in D2D communications -- 7.2.2. The data exchange phase in D2D communications -- 7.2.3. Investigations into future mobile networks -- 7.3. The context for machine learning and deep learning -- 7.3.1. Overview of deep learning and its application -- 7.3.2. Types of machine learning -- 7.3.3. Linear regression and classification -- 7.4. Dynamic discovery -- 7.4.1. Real-time prediction of user density -- 7.4.2. The dynamic discovery algorithm -- 7.5. Experimental results -- 7.5.1. General hypotheses -- 7.5.2. Traffic with low user density -- 7.5.3. Traffic with high user density -- 7.6. Conclusion -- 7.7. References -- 8 The Impact of Cognitive Radio on Green Networking: The Learning-through reinforcement Approach -- 8.1. Introduction -- 8.2. Green networking -- 8.2.1. Why should we reduce energy consumption? -- 8.2.2. Where can we reduce energy consumption? -- 8.2.3. Definition and objectives of green networking -- 8.3. Green strategies -- 8.3.1. Consolidation of resources -- 8.3.2. Selective connectivity -- 8.3.3. Virtualization -- 8.3.4. Energy-proportional computing -- 8.4. Green wireless networks -- 8.4.1. Energy efficiency in wireless networks -- 8.4.2. Controlling transmission power -- 8.5. How CR contributes to green networking -- 8.5.1. The principle behind CR. ; 8.5.2. The cognition cycle -- 8.5.3. Green networking in CR networks -- 8.6. Learning through reinforcement by taking into account energy efficiency during opportunistic access to the spectrum -- 8.6.1. Formulating the problem -- 8.6.2. Comparison between CR and Q_learning enabled CR -- 8.7. Conclusion -- 8.8. References -- List of Authors -- Index -- EULA.
• Titolo autorizzato: Service level management in emerging environments
• ISBN: 1-119-81832-X; 1-119-81834-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910830685603321
• Lo trovi qui: Univ. Federico II