Green Internet of Things (IoT) : Energy Efficiency Perspective.
- 1st ed.
- 1 online resource (194 pages)
- Wireless Networks Series .
- Wireless Networks Series .
Intro -- Preface -- Contents -- List of Acronyms -- 1 Introduction -- 2 Energy-Efficient Resource Allocationin for D2D Enabled Cellular Networks -- 2.1 Energy-Efficient Resource Allocation Problem -- 2.1.1 System Model -- 2.1.2 Problem Formulation -- 2.2 Energy-Efficient Stable Matching for D2D Communications -- 2.2.1 Preference Establishment -- 2.2.2 Energy-Efficient Stable Matching -- 2.3 Performance Results and Discussions -- 3 Energy Harvesting Enabled Energy Efficient Cognitive Machine-to-Machine Communications -- 3.1 Framework of Energy-Efficient Resource Allocation for EH-Based CM2M -- 3.1.1 Data Transmission Model -- 3.1.2 Energy Harvesting and Energy Consumption Model -- 3.1.3 Energy Efficient Resource Allocation Problem Formulation -- 3.2 Energy Efficient Joint Channel Selection, Peer Discovery, Power Control and Time Allocation for EH-CM2M Communications -- 3.2.1 Matching Based Problem Transformation -- 3.2.2 First-Stage Joint Power Control and Time Allocation Optimization -- 3.2.3 Preference List Construction -- 3.2.4 Second-Stage Joint Channel Selection and Peer Discovery Based on Matching -- 3.3 Performance Results and Discussions -- 3.3.1 Improve Average Energy Efficiency of M2M-TXs -- 3.3.2 Improve Average Energy Efficiency of M2M Pairs -- 4 Software Defined Machine-to-Machine Communication for Smart Energy Management in Power Grids -- 4.1 Framework of Energy-Efficient SD-M2M for Smart Energy Management -- 4.1.1 Architecture Overview -- 4.1.2 The Benefits of the SD-M2M -- 4.2 Software-Defined M2M Communication for Smart Energy Management Applications -- 4.3 Case Study and Analysis -- 4.3.1 Improve Spectral Efficiency -- 4.3.2 Reduce the Total Energy Generation Cost -- 5 Energy-Efficient M2M Communications in for Industrial Automation -- 5.1 Framework of Energy-Efficient M2M Communications. 5.2 Contract-Based Incentive Mechanism Design for AccessControl -- 5.2.1 MTC Type Modeling -- 5.2.2 Contract Formulation -- 5.2.3 Contract Optimization -- 5.3 Resource Allocation Base on Lyapunov Optimization and Matching Theory -- 5.3.1 Dynamic Queue Model -- 5.3.2 Problem Formulation and Transformation -- 5.3.3 Joint Rate Control, Power Allocation and Channel Selection -- Rate Control -- Joint Power Allocation and Channel Selection -- 5.4 Performance Results and Discussions -- 5.4.1 Feasibility and Efficiency of Access ControlMechanism -- 5.4.2 Feasibility and Efficiency of Resource Allocation Scheme -- 6 Energy-Efficient Context-Aware Resource Allocation for Edge-Computing-Empowered Industrial IoT -- 6.1 Framework of Energy-Efficient Edge-Computing-Empowered IIoT -- 6.1.1 System Model -- Task Transmission Model -- Energy Consumption Model -- Delay Model -- Service Reliability Requirement Model -- 6.1.2 Problem Formulation -- 6.2 Learning-Based Context-Aware Channel Selection for the Single-MTD Scenario -- 6.2.1 Lyapunov Based Problem Transformation -- 6.2.2 SEB-GSI Algorithm for the Ideal Case -- 6.2.3 SEB-UCB Algorithm for the Nonideal Case -- 6.3 Learning-Based Context-Aware Channel Selection for the Multi-MTD Scenario -- 6.3.1 SEB-MGSI Algorithm for the Ideal Case -- 6.3.2 SEBC-MUCB Algorithm for the Nonideal Case -- 6.4 Performance Results and Discussions -- 6.4.1 Performance Under the Single-MTD Scenario -- 6.4.2 Performance Under the Multi-MTD Scenario -- 7 Licensed and Unlicensed Spectrum Management for Energy-Efficient Cognitive M2M -- 7.1 Framework of CM2M Network -- 7.1.1 System Model -- 7.1.2 Problem Formulation -- 7.2 Context-Aware Learning-Based Channel Selection for CM2M -- 7.2.1 Problem Transformation -- 7.2.2 C2-GSI for Channel Selection with GSI -- 7.2.3 C2-EXP3 for Channel Selection with LocalInformation. 7.3 Performance Results and Discussions -- 8 Energy-Efficient Task Assignment and Route Planning for UAV -- 8.1 Framework of UAV-Aided MCS Systems -- 8.1.1 The Utility Function of the MCS Carrier -- 8.1.2 The Utility Function of UAVs -- 8.1.3 UAV-Aided MCS Systems Problem Formulation -- 8.2 Energy-Efficient Joint Task Assignment and Route Planning -- 8.2.1 Problem Transformation -- 8.2.2 The Route Planning -- 8.2.3 Preference List Construction -- 8.2.4 GS Based Second-Stage Task Assignment -- 8.3 Performance Results and Discussions -- 9 Energy-Efficient and Secure Resource Allocation for Multiple-Antenna NOMA with Wireless Power Transfer -- 9.1 Framework of Energy-Efficient and Secure Resource Allocation for Multiple-Antenna NOMA with Wireless Power Transfer -- 9.1.1 System Model -- 9.1.2 Problem Formulation -- 9.2 The Energy-Efficient and Secure Resource Allocation Scheme -- 9.2.1 Transformation of the Optimization Problem -- 9.2.2 Proposed Algorithmic Solution -- 9.3 Performance Evaluation -- 9.3.1 Improve Secure Data Rate -- 9.3.2 Improve the Energy Efficiency -- 10 Dynamic Computation Offloading Scheme for Fog Computing System with Energy Harvesting Devices -- 10.1 Framework of Socially Aware Dynamic Computation Offloading for Fog Computing System with EH Devices -- 10.1.1 System Movel -- 10.1.2 Problem Formulation -- 10.2 Proposed Solution -- 10.3 Performance Evaluation -- 11 Energy-Efficient Resource Allocation for Wireless Powered Massive MIMO System with Imperfect CSI -- 11.1 Framework of Resource Allocation for Wireless Powered Massive MIMO System with Imperfect CSI -- 11.1.1 System Model -- 11.1.2 Throughput Analysis -- 11.1.3 Problem Formulation -- 11.2 Proposed Antenna Selection and Resource Allocation Scheme -- 11.2.1 Proposed Antenna Selection Algorithm -- 11.2.2 Power and Time Allocation Schemes -- 11.3 Performance Evaluation. 12 Summary -- References.