The Smart Cyber Ecosystem for Sustainable Development

1. Auflage 2021
ISBN: 978-1-119-76164-8
Verlag: Wiley

Buch, Englisch, 480 Seiten, Format (B × H): 152 mm x 231 mm, Gewicht: 726 g

Das Cyber-Ökosystem kann unser natürliches Ökosystem nachbilden, in dem verschiedene lebende und nicht lebende Dinge miteinander interagieren, um bestimmte Aufgaben zu erfüllen. Ganz ähnlich arbeiten die verschiedenen Einheiten des Cyber-Ökosystems auf digitaler Ebene zusammen, um unseren Lebensstil durch die Schaffung intelligenter und automatisierter Systeme/Prozesse zu revolutionieren. Die Hauptakteure des Cyber-Ökosystems sind insbesondere das Internet der Dinge (IoT), die künstliche Intelligenz (KI) und Mechanismen zur Gewährleistung der Cybersicherheit.

In diesem Buch wird aufgezeigt, wie die Kombination dieser Technologien eine digitale, nachhaltige sozioökonomische Infrastruktur ermöglicht, die unsere Lebensqualität verbessert. Es werden fortschrittliche Automatisierungsmethoden vorgestellt, die mit verbesserten Geschäfts- und Prüfungsmodellen, universellen Authentifizierungsschemata, transparenter Governance und innovativen Prognosen einhergehen.

Autoren/Hrsg.

Kumar, Pardeep

Jain, Vishal

Ponnusamy, Vasaki

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Verfahrenstechnik, Chemieingenieurwesen

Inhaltsverzeichnis

Preface xxi

Part 1: Internet of Things 1

1 Voyage of Internet of Things in the Ocean of Technology 3
Tejaskumar R. Ghadiyali, Bharat C. Patel and Manish M. Kayasth

1.1 Introduction 3

1.1.1 Characteristics of IoT 4

1.1.2 IoT Architecture 5

1.1.3 Merits and Demerits of IoT 6

1.2 Technological Evolution Toward IoT 7

1.3 IoT-Associated Technology 8

1.4 Interoperability in IoT 14

1.5 Programming Technologies in IoT 15

1.5.1 Arduino 15

1.5.2 Raspberry Pi 17

1.5.3 Python 18

1.6 IoT Applications 19

Conclusion 22

References 22

2 AI for Wireless Network Optimization: Challenges and Opportunities 25
Murad Abusubaih

2.1 Introduction to AI 25

2.2 Self-Organizing Networks 27

2.2.1 Operation Principle of Self-Organizing Networks 27

2.2.2 Self-Configuration 28

2.2.3 Self-Optimization 28

2.2.4 Self-Healing 28

2.2.5 Key Performance Indicators 29

2.2.6 SON Functions 29

2.3 Cognitive Networks 29

2.4 Introduction to Machine Learning 30

2.4.1 ML Types 31

2.4.2 Components of ML Algorithms 31

2.4.3 How do Machines Learn? 32

2.4.3.1 Supervised Learning 32

2.4.3.2 Unsupervised Learning 33

2.4.3.3 Semi-Supervised Learning 35

2.4.3.4 Reinforcement Learning 35

2.4.4 ML and Wireless Networks 36

2.5 Software-Defined Networks 36

2.5.1 SDN Architecture 37

2.5.2 The OpenFlow Protocol 38

2.5.3 SDN and ML 39

2.6 Cognitive Radio Networks 39

2.6.1 Sensing Methods 41

2.7 ML for Wireless Networks: Challenges and Solution Approaches 41

2.7.1 Cellular Networks 42

2.7.1.1 Energy Saving 42

2.7.1.2 Channel Access and Assignment 42

2.7.1.3 User Association and Load Balancing 43

2.7.1.4 Traffic Engineering 44

2.7.1.5 QoS/QoE Prediction 45

2.7.1.6 Security 45

2.7.2 Wireless Local Area Networks 46

2.7.2.1 Access Point Selection 47

2.7.2.2 Interference Mitigation 48

2.7.2.3 Channel Allocation and Channel Bonding 49

2.7.2.4 Latency Estimation and Frame Length Selection 49

2.7.2.5 Handover 49

2.7.3 Cognitive Radio Networks 50

References 50

3 An Overview on Internet of Things (IoT) Segments and Technologies 57
Amarjit Singh

3.1 Introduction 57

3.2 Features of IoT 59

3.3 IoT Sensor Devices 59

3.4 IoT Architecture 61

3.5 Challenges and Issues in IoT 62

3.6 Future Opportunities in IoT 63

3.7 Discussion 64

3.8 Conclusion 65

References 65

4 The Technological Shift: AI in Big Data and IoT 69
Deepti Sharma, Amandeep Singh and Sanyam Singhal

4.1 Introduction 69

4.2 Artificial Intelligence 71

4.2.1 Machine Learning 71

4.2.2 Further Development in the Domain of Artificial Intelligence 73i

4.2.3 Programming Languages for Artificial Intelligence 74

4.2.4 Outcomes of Artificial Intelligence 74

4.3 Big Data 75

4.3.1 Artificial Intelligence Methods for Big Data 77

4.3.2 Industry Perspective of Big Data 77

4.3.2.1 In Medical Field 78

4.3.2.2 In Meteorological Department 78

4.3.2.3 In Industrial/Corporate Applications and Analytics 79

4.3.2.4 In Education 79

4.3.2.5 In Astronomy 79

4.4 Internet of Things 80

4.4.1 Interconnection of IoT With AoT 81

4.4.2 Difference Between IIoT and IoT 81

4.4.3 Industrial Approach for IoT 82

4.5 Technical Shift in AI, Big Data, and IoT 82

4.5.1 Industries Shifting to AI-Enabled Big Data Analytics 83

4.5.2 Industries Shifting to AI-Powered IoT Devices 84

4.5.3 Statistical Data of These Shifts 84

4.6 Conclusion 85

References 86

5 IoT’s Data Processing Using Spark 91
Ankita Bansal and Aditya Atri

5.1 Introduction 91

Über Autor(innen)

Pardeep Kumar is a Professor and Head of the Software Engineering Department and Director ORIC, Quaid-e-Awam University of Engineering, Science & Technology (QUEST) Nawabshah, Pakistan. He completed his PhD from Berlin, Germany in 2012. He has authored more than 50 research publications in reputed journals and conferences around the world including three books and several book chapters.

Vishal Jain PhD is an associate professor in the Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, U.P. India. He has authored more than 85 research papers in reputed conferences and journals, and has authored and edited more than 10 books.
Vasaki Ponnusamy is an assistant professor in the Universiti Tunku Abdul Rahman, Malaysia where she heads the Department of Computer and Communication Technology. She obtained her PhD in IT from Universiti Teknologi PETRONAS (UTP), Malaysia (2013).