Resource management for on-demand mission-critical internet of things applications / / Junaid Farooq, Quanyan Zhu

• Record Nr.: UNINA9910830377003321
• Autore: Farooq Junaid
• Pubbl/distr/stampa: Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2021]; ©2021
• ISBN: 1-119-71612-8; 1-119-71611-X; 1-119-71610-1
• Descrizione fisica: 1 online resource (227 pages)
• Collana: IEEE Press
• Disciplina: 004.678
• Soggetti: Internet of things
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Cover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- Acronyms -- Part I Introduction -- Chapter 1 Internet of Things‐Enabled Systems and Infrastructure -- 1.1 Cyber-Physical Realm of IoT -- 1.2 IoT in Mission‐Critical Applications -- 1.3 Overview of the Book -- 1.3.1 Main Topics -- 1.3.1.1 Dynamic Reservation of Wireless Spectrum Resources -- 1.3.1.2 Dynamic Cross‐Layer Connectivity Using Aerial Networks -- 1.3.1.3 Dynamic Processes Over Multiplex Spatial Networks and Reconfigurable Design -- 1.3.1.4 Sequential Resource Allocation Under Spatio‐Temporal Uncertainties -- 1.3.2 Notations -- Chapter 2 Resource Management in IoT‐Enabled Interdependent Infrastructure -- 2.1 System Complexity and Scale -- 2.2 Network Geometry and Dynamics -- 2.3 On‐Demand MC‐IoT Services and Decision Avenues -- 2.4 Performance Metrics -- 2.5 Overview of Scientific Methodologies -- Part II Design Challenges in MC‐IoT -- Chapter 3 Wireless Connectivity Challenges -- 3.1 Spectrum Scarcity and Reservation Based Access -- 3.2 Connectivity in Remote Environments -- 3.3 IoT Networks in Adversarial Environments -- Chapter 4 Resource and Service Provisioning Challenges -- 4.1 Efficient Allocation of Cloud Computing Resources -- 4.2 Dynamic Pricing in the Cloud -- 4.3 Spatio‐Temporal Urban Service Provisioning -- Part III Wireless Connectivity Mechanisms for MC‐IoT -- Chapter 5 Reservation‐; Based Spectrum Access Contracts -- 5.1 Reservation of Time-Frequency Blocks in the Spectrum -- 5.1.1 Network Model -- 5.1.2 Utility of Spectrum Reservation -- 5.2 Dynamic Contract Formulation -- 5.2.1 Objective of Network Operator -- 5.2.2 Spectrum Reservation Contract -- 5.2.2.1 Operator Profitability -- 5.2.2.2 IC and IR Constraints -- 5.2.3 Optimal Contracting Problem -- 5.2.4 Solution to the Optimization Problem -- 5.3 Mission‐Oriented Pricing and Refund Policies.; 5.4 Summary and Conclusion -- Chapter 6 Resilient Connectivity of IoT Using Aerial Networks -- 6.1 Connectivity in the Absence of Backhaul Networks -- 6.2 Aerial Base Station Modeling -- 6.3 Dynamic Coverage and Connectivity Mechanism -- 6.3.1 MAP-MSD Matching -- 6.3.2 MAP Dynamics and Objective -- 6.3.3 Controller Design -- 6.3.3.1 Attractive and Repulsive Function -- 6.3.3.2 Velocity Consensus Function -- 6.3.4 Individual Goal Function -- 6.3.5 Cluster Centers -- 6.4 Performance Evaluation and Simulation Results -- 6.4.1 Results and Discussion -- 6.4.1.1 Simulation Parameters -- 6.4.1.2 Resilience -- 6.4.1.3 Comparison -- 6.5 Summary and Conclusion -- Part IV Secure Network Design Mechanisms -- Chapter 7 Wireless IoT Network Design in Adversarial Environments -- 7.1 Adversarial Network Scenarios -- 7.2 Modeling Device Capabilities and Network Heterogeneity -- 7.2.1 Network Geometry -- 7.2.2 Network Connectivity -- 7.2.2.1 Intra‐layer Connectivity -- 7.2.2.2 Network‐wide Connectivity -- 7.3 Information Dissemination Under Attacks -- 7.3.1 Information Dynamics -- 7.3.1.1 Single Message Propagation -- 7.3.1.2 Multiple Message Propagation -- 7.3.2 Steady State Analysis -- 7.4 Mission‐Specific Network Optimization -- 7.4.1 Equilibrium Solution -- 7.4.2 Secure and Reconfigurable Network Design -- 7.5 Simulation Results and Validation -- 7.5.1 Mission Scenarios -- 7.5.1.1 Intelligence -- 7.5.1.2 Encounter Battle -- 7.6 Summary and Conclusion -- Chapter 8 Network Defense Mechanisms Against Malware Infiltration -- 8.1 Malware Infiltration and Botnets -- 8.1.1 Network Model -- 8.1.2 Threat Model -- 8.2 Propagation Modeling and Analysis -- 8.2.1 Modeling of Malware and Information Evolution -- 8.2.2 State Space Representation and Dynamics -- 8.2.3 Analysis of Equilibrium State -- 8.3 Patching Mechanism for Network Defense -- 8.3.1 Simulation Results.; 8.3.2 Simulation and Validation -- 8.4 Summary and Conclusion -- Part V Resource Provisioning Mechanisms -- Chapter 9 Revenue Maximizing Cloud Resource Allocation -- 9.1 Cloud Service Provider Resource Allocation Problem -- 9.2 Allocation and Pricing Rule -- 9.3 Dynamic Revenue Maximization -- 9.3.1 Adaptive and Resilient Allocation and Pricing Policy -- 9.4 Numerical Results and Discussions -- 9.5 Summary and Conclusion -- Chapter 10 Dynamic Pricing of Fog‐Enabled MC‐IoT Applications -- 10.1 Edge Computing and Delay Modeling -- 10.2 Allocation Efficiency and Quality of Experience -- 10.2.1 Allocation Policy -- 10.2.2 Pricing Policy -- 10.3 Optimal Allocation and Pricing Rules -- 10.3.1 Single VMI Case -- 10.3.2 Multiple VMI Case -- 10.3.3 Expected Revenue -- 10.3.4 Implementation of Dynamic VMI Allocation and Pricing -- 10.4 Numerical Experiments and Discussion -- 10.4.1 Experiment Setup -- 10.4.2 Simulation Results -- 10.4.3 Comparison with Other Approaches -- 10.5 Summary and Conclusion -- Chapter 11 Resource Provisioning to Spatio‐Temporal Urban Services -- 11.1 Spatio‐Temporal Modeling of Urban Service Requests -- 11.1.1 Characterization of Service Requests -- 11.1.2 Utility of Resource Allocation -- 11.1.3 Problem Definition -- 11.2 Optimal Dynamic Allocation Mechanism -- 11.2.1 Dynamic Programming Solution -- 11.2.2 Computation and Implementation -- 11.3 Numerical Results ; and Discussion -- 11.3.1 Special Cases -- 11.3.1.1 Power Law Utility -- 11.3.1.2 Exponential Utility -- 11.3.2 Performance Evaluation and Comparison -- 11.4 Summary and Conclusions -- Part VI Conclusion -- Chapter 12 Challenges and Opportunities in the IoT Space -- 12.1 Broader Insights and Future Directions -- 12.1.1 Distributed Cross‐Layer Intelligence for Mission‐Critical IoT Services -- 12.1.1.1 Secure and Resilient Networking for Massive IoT Networks.; 12.1.1.2 Autonomic Networked CPS: From Military to Civilian Applications -- 12.1.1.3 Strategic Resource Provisioning for Mission‐Critical IoT Services -- 12.2 Future Research Directions -- 12.2.1 Distributed Learning and Data Fusion for Security and Resilience in IoT‐Driven Urban Applications -- 12.2.1.1 Data‐Driven Learning and Decision‐Making for Smart City Service Provisioning -- 12.2.1.2 Market Design for On‐Demand and Managed IoT‐Enabled Urban Services -- 12.2.1.3 Proactive Resiliency Planning and Learning for Disaster Management in Cities -- 12.2.2 Supply Chain Security and Resilience of IoT -- 12.3 Concluding Remarks -- Bibliography -- Index -- EULA.
• Sommario/riassunto: "The Internet of things (IoT) is an emerging paradigm that allows the interconnection of devices, which are equipped with electronic sensors and actuators. There is a plethora of resources, at each stage of the IoT ecosystem, which need to be managed effectively to cater for the demands of potentially mission-critical (MC) applications. Service requests often appear randomly over time and space with varying intensity. Resource provisioning decisions need to be made strategically in real-time, particularly when there is incomplete information about the time, location, and intensity of future requests. Resource management has traditionally been focused on dealing with objectives such as efficiency, capacity, throughput, etc., in mind. However, often the underlying incentives and economic aspects have been ignored"--