RESOURCE MANAGEMENT FOR ON-DEMAND MISSION-CRITICAL INTERNET OF THINGS APPLICATIONS Discover an insightful and up-to-date treatment of resource management in Internet of Things technology In Resource Management for On-Demand Mission-Critical Internet of Things Applications, an expert team of engineers delivers an insightful analytical perspective on modeling and decision support for mission-critical Internet of Things applications. The authors dissect the complex IoT ecosystem and provide a cross-layer perspective on the design and operation of IoT, especially in the context of smart and…mehr
RESOURCE MANAGEMENT FOR ON-DEMAND MISSION-CRITICAL INTERNET OF THINGS APPLICATIONS Discover an insightful and up-to-date treatment of resource management in Internet of Things technology In Resource Management for On-Demand Mission-Critical Internet of Things Applications, an expert team of engineers delivers an insightful analytical perspective on modeling and decision support for mission-critical Internet of Things applications. The authors dissect the complex IoT ecosystem and provide a cross-layer perspective on the design and operation of IoT, especially in the context of smart and connected communities. The book offers an economic perspective on resource management in IoT systems with a particular emphasis on three main areas: spectrum management via reservation, allocation of cloud/fog resources to IoT applications, and resource provisioning to smart city service requests. It leverages theories from dynamic mechanism design, optimal control theory, and spatial point processes, providing an overview of integrated decision-making frameworks. Finally, the authors discuss future directions and relevant problems on the economics of resource management from new perspectives, like security and resilience. Readers will also enjoy the inclusion of: * A thorough introduction and overview of IoT applications in smart cities, mission critical IoT services and requirements, and key metrics and research challenges * A comprehensive exploration of the allocation of spectrum resources to mission critical IoT applications, including the massive surge of IoT and spectrum scarcity problem * Practical discussions of the provisioning of cloud/fog computing resources to IoT applications, including allocation policy * In-depth examinations of resource provisioning to spatio-temporal service requests in smart cities Perfect for engineers working on Internet of Things and cyber-physical systems, Resource Management for On-Demand Mission-Critical Internet of Things Applications is also an indispensable reference for graduate students, researchers, and professors with an interest in IoT resource management.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Junaid Farooq is an Assistant Professor with the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn. His research focus is on system level modeling, analysis, and the optimization of wireless communication networks. Quanyan Zhu, PhD, is Associate Professor with the Department of Electrical and Computer Engineering at New York University.
Inhaltsangabe
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 Trim Size: 6in x 9in Single Column Farooq716099 ftoc.tex V1 - 06/02/2021 12:07pm Page viii _ _ _ _ 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 Trim Size: 6in x 9in Single Column Farooq716099 ftoc.tex V1 - 06/02/2021 12:07pm Page ix _ _ _ _ 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 Trim Size: 6in x 9in Single Column Farooq716099 ftoc.tex V1 - 06/02/2021 12:07pm Page x _ _ _ _ x Contents 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 Trim Size: 6in x 9in Single Column Farooq716099 ftoc.tex V1 - 06/02/2021 12:07pm Page xi _ _ _ _ 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 _
