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Resource Management for On-Demand Mission-Critical Internet of Things Applications. Edition No. 1. Wiley - IEEE

  • ID: 5351661
  • Book
  • January 2022
  • 256 Pages
  • John Wiley and Sons Ltd

This book provides an analytical perspective on modeling and decision support for mission-critical Internet of Things (MC-IoT) applications. It dissects the complex IoT ecosystem and provides a cross-layer perspective on the design and operation of IoT, particularly in the context of smart and connected communities. The book provides an economic perspective on the resource management in IoT systems with particular emphasis on mission-critical services and applications. It considers three main areas of resource management in MC-IoT, i.e., spectrum management via reservation, allocation of cloud/fog resources to IoT applications, and resource provisioning to smart city service requests. Leveraging theories from dynamic mechanism design, optimal control theory, and spatial point processes, this book provides an overview of integrated decision-making frameworks that deal with resource management from an economic perspective. The book concludes with discussing future directions and relevant problems on the economics of resource management from new perspectives such as security and resilience.

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Preface xiii

Acknowledgments xvii

Acronyms xix

Part I Introduction 1

1 Internet of Things-Enabled Systems and Infrastructure 3

1.1 Cyber–Physical Realm of IoT 3

1.2 IoT in Mission-Critical Applications 4

1.3 Overview of the Book 4

1.3.1 Main Topics 5

1.3.1.1 Dynamic Reservation ofWireless Spectrum Resources 5

1.3.1.2 Dynamic Cross-Layer Connectivity Using Aerial Networks 5

1.3.1.3 Dynamic Processes Over Multiplex Spatial Networks and

Reconfigurable Design 6

1.3.1.4 Sequential Resource Allocation Under Spatio-Temporal

Uncertainties 7

1.3.2 Notations 8

2 Resource Management in IoT-Enabled Interdependent

Infrastructure 9

2.1 System Complexity and Scale 9

2.2 Network Geometry and Dynamics 10

2.3 On-Demand MC-IoT Services and Decision Avenues 11

2.4 Performance Metrics 12

2.5 Overview of Scientific Methodologies 12

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viii Contents

Part II Design Challenges in MC-IoT 15

3 Wireless Connectivity Challenges 17

3.1 Spectrum Scarcity and Reservation Based Access 17

3.2 Connectivity in Remote Environments 19

3.3 IoT Networks in Adversarial Environments 22

4 Resource and Service Provisioning Challenges 25

4.1 Efficient Allocation of Cloud Computing Resources 25

4.2 Dynamic Pricing in the Cloud 27

4.3 Spatio-Temporal Urban Service Provisioning 31

Part III Wireless Connectivity Mechanisms for MC-IoT 35

5 Reservation-Based Spectrum Access Contracts 37

5.1 Reservation of Time–Frequency Blocks in the Spectrum 37

5.1.1 Network Model 38

5.1.2 Utility of Spectrum Reservation 39

5.2 Dynamic Contract Formulation 39

5.2.1 Objective of Network Operator 40

5.2.2 Spectrum Reservation Contract 40

5.2.2.1 Operator Profitability 40

5.2.2.2 IC and IR Constraints 41

5.2.3 Optimal Contracting Problem 41

5.2.4 Solution to the Optimization Problem 42

5.3 Mission-Oriented Pricing and Refund Policies 44

5.4 Summary and Conclusion 47

6 Resilient Connectivity of IoT Using Aerial Networks 49

6.1 Connectivity in the Absence of Backhaul Networks 49

6.2 Aerial Base Station Modeling 50

6.3 Dynamic Coverage and ConnectivityMechanism 52

6.3.1 MAP–MSD Matching 53

6.3.2 MAP Dynamics and Objective 54

6.3.3 Controller Design 55

6.3.3.1 Attractive and Repulsive Function 55

6.3.3.2 Velocity Consensus Function 56

6.3.4 Individual Goal Function 56

6.3.5 Cluster Centers 57

6.4 Performance Evaluation and Simulation Results 58

6.4.1 Results and Discussion 59

6.4.1.1 Simulation Parameters 59

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Contents ix

6.4.1.2 Resilience 61

6.4.1.3 Comparison 64

6.5 Summary and Conclusion 68

Part IV Secure Network DesignMechanisms 69

7 Wireless IoT Network Design in Adversarial

Environments 71

7.1 Adversarial Network Scenarios 71

7.2 Modeling Device Capabilities and Network Heterogeneity 71

7.2.1 Network Geometry 72

7.2.2 Network Connectivity 73

7.2.2.1 Intra-layer Connectivity 73

7.2.2.2 Network-wide Connectivity 74

7.3 Information Dissemination Under Attacks 76

7.3.1 Information Dynamics 77

7.3.1.1 Single Message Propagation 78

7.3.1.2 MultipleMessage Propagation 79

7.3.2 Steady State Analysis 80

7.4 Mission-Specific Network Optimization 81

7.4.1 Equilibrium Solution 81

7.4.2 Secure and Reconfigurable Network Design 87

7.5 Simulation Results and Validation 91

7.5.1 Mission Scenarios 92

7.5.1.1 Intelligence 92

7.5.1.2 Encounter Battle 93

7.6 Summary and Conclusion 96

8 Network DefenseMechanisms Against Malware

Infiltration 97

8.1 Malware Infiltration and Botnets 97

8.1.1 Network Model 97

8.1.2 Threat Model 99

8.2 PropagationModeling and Analysis 101

8.2.1 Modeling of Malware and Information Evolution 101

8.2.2 State Space Representation and Dynamics 102

8.2.3 Analysis of Equilibrium State 104

8.3 Patching Mechanism for Network Defense 109

8.3.1 Simulation Results 115

8.3.2 Simulation and Validation 120

8.4 Summary and Conclusion 124

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Part V Resource ProvisioningMechanisms 125

9 Revenue Maximizing Cloud Resource Allocation 127

9.1 Cloud Service Provider Resource Allocation Problem 127

9.2 Allocation and Pricing Rule 128

9.3 Dynamic Revenue Maximization 129

9.3.1 Adaptive and Resilient Allocation and Pricing Policy 134

9.4 Numerical Results and Discussions 135

9.5 Summary and Conclusion 139

10 Dynamic Pricing of Fog-Enabled MC-IoT Applications 141

10.1 Edge Computing and Delay Modeling 142

10.2 Allocation Efficiency and Quality of Experience 143

10.2.1 Allocation Policy 144

10.2.2 Pricing Policy 145

10.3 Optimal Allocation and Pricing Rules 146

10.3.1 Single VMI Case 146

10.3.2 Multiple VMI Case 149

10.3.3 Expected Revenue 155

10.3.4 Implementation of Dynamic VMI Allocation and

Pricing 156

10.4 Numerical Experiments and Discussion 158

10.4.1 Experiment Setup 158

10.4.2 Simulation Results 158

10.4.3 Comparison with Other Approaches 160

10.5 Summary and Conclusion 164

11 Resource Provisioning to Spatio-Temporal Urban

Services 165

11.1 Spatio-TemporalModeling of Urban Service Requests 165

11.1.1 Characterization of Service Requests 166

11.1.2 Utility of Resource Allocation 167

11.1.3 Problem Definition 169

11.2 Optimal Dynamic Allocation Mechanism 169

11.2.1 Dynamic Programming Solution 170

11.2.2 Computation and Implementation 172

11.3 Numerical Results and Discussion 174

11.3.1 Special Cases 174

11.3.1.1 Power Law Utility 174

11.3.1.2 Exponential Utility 176

11.3.2 Performance Evaluation and Comparison 178

11.4 Summary and Conclusions 180

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Contents xi

Part VI Conclusion 183

12 Challenges and Opportunities in the IoT Space 185

12.1 Broader Insights and Future Directions 185

12.1.1 Distributed Cross-Layer Intelligence for Mission-Critical IoT

Services 185

12.1.1.1 Secure and Resilient Networking for Massive IoT Networks 185

12.1.1.2 Autonomic Networked CPS: From Military to Civilian

Applications 186

12.1.1.3 Strategic Resource Provisioning for Mission-Critical IoT

Services 187

12.2 Future Research Directions 187

12.2.1 Distributed Learning and Data Fusion for Security and Resilience in

IoT-Driven Urban Applications 188

12.2.1.1 Data-Driven Learning and Decision-Making for Smart City Service

Provisioning 188

12.2.1.2 Market Design for On-Demand and Managed IoT-Enabled Urban

Services 189

12.2.1.3 Proactive Resiliency Planning and Learning for Disaster

Management in Cities 190

12.2.2 Supply Chain Security and Resilience of IoT 190

12.3 Concluding Remarks 191

Bibliography 193

Index 207

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Muhammad Junaid Farooq
Quanyan Zhu
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