ENGLISH

Software Defined Internet of Everything

Book information

Publisher
Springer
Year
2022
ISBN
3030893278, 9783030893279
Language
english
Format
PDF
Filesize
8 MB (7886384 bytes)
Series
Internet of Things
Edition
1st ed. 2022
Pages
317\301
Time added
2022-01-19 06:17:39

Description

This book provides comprehensive discussion on key topics related to the usage and deployment of software defined networks (SDN) in Internet of Everything applications like, healthcare systems, data centers, edge/fog computing, vehicular networks, intelligent transportation systems, smart grids, smart cities and more. The authors provide diverse solutions to overcome challenges of conventional network binding in various Internet of Everything applications where there is need of an adaptive, agile, and flexible network backbone. The book showcases different deployment models, algorithms and implementations related to the usage of SDN in Internet of Everything applications along with the pros and cons of the same. Even more, this book provides deep insights into the architecture of software defined networking specifically about the layered architecture and different network planes, logical interfaces, and programmable operations. The need of network virtualization and the deployment models for network function virtualization is also included with an aim towards the design of interoperable network architectures by researchers in future. Uniquely, the authors find hands on practical implementation, deployment scenarios and use cases for various software defined networking architectures in Internet of Everything applications like healthcare networks, Internet of Things, intelligent transportation systems, smart grid, underwater acoustic networks and many more. In the end, design and research challenges, open issues, and future research directions are provided in this book for a wide range of readers Foreword Preface Contents Contributors Part I Internet of Everything and Smart City 1 Internet of Everything: Background and Challenges 1.1 Introduction 1.1.1 Working of IoT 1.1.1.1 Sensors 1.1.1.2 Gateway Node 1.1.1.3 Data Processing and Analysis 1.1.1.4 End-User 1.1.2 Internet of Everything 1.2 Applications of Internet of Everything 1.3 Challenges of Internet of Everything 1.4 Conclusion References 2 Smart Cities, Connected World, and Internet of Things 2.1 Introduction 2.2 Smart City Integrated Perspective 2.2.1 Smart City Overview 2.2.2 Smart Cities Goals and Barriers 2.2.3 Digitalization and Connected World 2.3 IoT Enabling Smart Cities 2.4 Case Studies References Part II Software-Defined Networking 3 Challenges of Traditional Networks and Development of Programmable Networks 3.1 Introduction 3.2 Traditional Network Architecture 3.2.1 Internet Development History 3.2.2 Equipment Development History 3.2.3 Typical Architecture 3.2.3.1 Home Network 3.2.3.2 Campus Network 3.2.3.3 Government Affairs Network 3.2.3.4 Data Center Network 3.2.4 Conclusion of Issues 3.3 SDN Network Architecture 3.3.1 Development Path 3.3.2 Definition and Architecture 3.3.3 Core Technology and Advantages 3.3.3.1 Core Technology 3.3.3.2 The Main Advantages 3.3.4 Industry Chain Analysis 3.4 Application Scenario Analysis 3.4.1 Application of SDN in Data Center Network 3.4.2 Application of SDN in Government and Enterprise Networks 3.4.3 Application of SDN in Telecom Operator Network 3.4.4 Application of SDN in Network Virtualization Technology 3.5 Future and Challenges 3.5.1 Existing Challenges 3.5.1.1 Security Issues 3.5.1.2 Standardization Issues 3.5.1.3 Performance Issues 3.5.2 Future Development 3.6 Conclusion References 4 Architecture and Deployment Models-SDN Protocols, APIs, and Layers, Applications and Implementations 4.1 Introduction 4.2 SDN Architecture 4.3 SDN Protocols 4.4 Principles of SDN Architecture 4.5 SDN Tools and Languages 4.6 SDN Benefits and Application Domains 4.7 Research Challenges References 5 Network Policies in Software Defined Internet of Everything 5.1 Introduction 5.1.1 What are the Network Policies? 5.1.2 Role and Importance of Network Policies 5.1.2.1 Business Intent and Agility 5.1.2.2 Consistent Services 5.1.2.3 Network Automation 5.1.2.4 Performance Monitoring 5.1.2.5 Network Security 5.2 Types of Network Policies for IoE 5.2.1 Security and Access Control 5.2.2 Application and QoS 5.2.3 Traffic Routing and Service Insertion 5.2.4 IP-Based Versus Group- or Role-Based 5.2.5 Standard Usage Policy 5.2.6 Disaster Recovery Policy 5.2.7 Backup Policy 5.2.8 Archiving Policy 5.2.9 Failover Policy 5.3 Automation of Network Policies 5.4 Network Policies in SDN 5.5 Conflict and Overlapping Among the Network Policies 5.6 Network Policies Optimization 5.6.1 Detection and Settlement of Policy Variations 5.6.2 Fine-Tuning of Goal Policies 5.7 Conclusion References 6 Analysis of Load Balancing Techniques in Software-Defined Networking 6.1 Introduction 6.2 Software-Defined Network 6.2.1 Types of Software-Defined Network 6.2.1.1 Centralized SDN 6.2.1.2 Distributed SDN 6.2.1.3 Hybrid SDN 6.3 Techniques for Load Balancing in Software-Defined Network 6.3.1 Balance the Load by Filtering the Load Based on TCP and UDP 6:10 6.3.2 Stable the Network by Shifting the Workload from Overloaded Controller to the Underloaded Controllers 6:11 6.3.3 Balancing of Load by Authentication, Monitoring Load, and Switch Migration 6:12 6.3.4 Different Services Provided by Supervisor Controller to Local Controller for Load Sharing in Scalable Network 6:13 6.3.5 Load Balancing by Making Cluster of Controller by Super Controller 6:14 6.3.6 Lighten Up the Overloaded Controller by Migration of the Switches to Lightly Load by Broadcasting Load Between Controllers 6:15 6.3.7 Tenant Controllers Are Finding Best Paths by Calculating the Maximum Throughput 6:16 6.3.8 Balance the Flow of User's Load by a Different Method of Sharing Resources 6:17 6.3.9 Finding Best Path by Considering Bandwidth and Delay for Cloud Data Centers 6:11 6.4 Conclusion and Future Work References 7 Analysis of Energy Optimization Approaches in Internet of Everything: An SDN Prospective 7.1 Introduction 7.1.1 Applications and Types of IoT 7.2 Software-Defined Networking 7.3 Analysis of Various Energy-Efficient Techniques in SDN-Based Environment 7.4 Conclusion References 8 Network Function Virtualization 8.1 What Is Network Function Virtualization 8.2 NFV Architecture and Model 8.3 NFV Applications and Implementations 8.4 Resource Allocation in NFV-Enabled Networks References Part III Application of Software-Defined Networking in Cloud Computing 9 Prospective on Technical Considerations for Edge–Cloud Cooperation Using Software-Defined Networking 9.1 Introduction 9.2 Edge Computing 9.2.1 Technical Challenges for Edge Computing 9.3 Software-Defined Networking 9.3.1 Architecture 9.4 SDN-Edge Cooperation 9.4.1 Architecture 9.4.2 A Real Scenario of SDN-IoT-Edge Architecture 9.4.3 Benefits of Using SDN-IoT-Edge Platform 9.5 Technical Requirements of SDN-Edge vs Energy Efficiency 9.6 Stat of the Art 9.6.1 Cloud Computing 9.6.2 Edge Computing 9.6.3 SDN 9.6.4 SDN-Edge Cooperation 9.7 Conclusion References 10 Software-Defined Networking in Data Centers 10.1 Introduction 10.1.1 Software-Defined Networking: An Overview 10.1.2 SDN Building Blocks 10.1.2.1 SDN Switches 10.1.2.2 SDN Controllers 10.2 SDN Applications 10.2.1 Internet of Things 10.2.2 Home Networks 10.2.3 Cellular Networks 10.2.4 Optical Networks 10.3 Cloud Computing and Challenges 10.3.1 Cloud Computing and Service Models 10.3.2 Data Center Networks 10.3.3 Challenges in Data Center Networks 10.3.4 SDN in Data Center Networks 10.4 Routing and Traffic Engineering in Data Center Networks 10.4.1 Flow Management in Data Center Networks 10.4.2 Traffic Engineering in Data Center Networks 10.4.3 Load Balancing in Data Center Networks 10.4.4 Resource Management in Data Center Networks 10.4.5 Energy Management in Data Center Networks 10.5 Conclusions References 11 QoS-Aware Dynamic Flow Management in Software-Defined Data Center Networks 11.1 Introduction 11.2 Related Works 11.3 System Model 11.4 FASCES: QoS-Aware Dynamic Flow Management Scheme 11.4.1 Single-Leader-Multiple-Followers Stackelberg Game: The Justification 11.4.2 Game Formulation 11.4.3 Existence of Equilibrium 11.4.4 Proposed Workflow 11.5 Performance Evaluation 11.6 Conclusion References Part IV Security and Trust Applications for Software-Defined Networking 12 Trusted Mechanism Using Artificial Neural Networks in Healthcare Software-Defined Networks 12.1 Introduction 12.1.1 Contribution 12.2 Related Work 12.3 Proposed Approach 12.3.1 Back Propagation (BP) Algorithm 12.4 Performance Evaluation 12.4.1 Results and Discussion 12.5 Conclusion References 13 Stealthy Verification Mechanism to Defend SDN Against Topology Poisoning 13.1 Introduction 13.2 Related Work 13.3 Problem Statement 13.4 Proposed Solution 13.4.1 Methodology 13.5 Implementation 13.5.1 Software-Defined Network Setup 13.5.2 ESPV Implementation 13.5.3 Network Topology 13.6 Results and Analysis 13.6.1 Performance Analysis 13.6.2 Resource Consumption by ESPV Scheme 13.6.3 Applicability of ESPV in Real SDN Cloud Topology 13.7 Conclusion and Future Work References 14 Implementation of Protection Protocols for Security Threats in SDN 14.1 Introduction 14.2 Security Issues 14.3 Related Work 14.4 Problem Statement 14.5 Proposed Solution 14.6 Implementation 14.7 Conclusion References Part V Application Use Cases of Software-Defined Networking 15 SDVN-Based Smart Data Dissemination Model for High-Speed Road Networks 15.1 Introduction 15.2 Literature Review 15.3 The Proposed System Model 15.3.1 Working Model 15.3.2 Types of Services Provided by the Centralized Controller 15.4 Case Study: On-Demand Network Service for High-Speed Vehicles 15.5 Conclusion References 16 Advanced Deep Learning for Image Processing in Industrial Internet of Things Under Software-Defined Network 16.1 Introduction 16.2 Related Works 16.3 Method 16.3.1 Architecture and Key Technologies of IIoT 16.3.2 Dynamic Computing Framework of SDN-Based IIoT 16.3.3 Application of Software-Defined Internet of Everything 16.3.4 Image Processing System for Machine Vision of IIoT 16.3.5 Image Processing Technology Based on Deep Learning 16.4 Simulation Experiment 16.5 Results and Discussion 16.5.1 Comparison of Image Smoothing Technologies Based on Deep Learning 16.5.2 Classification Effect of Image Processing on Welding Defects in Industrial Production 16.6 Conclusions References Index

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