Energy Optimization Protocol Design for Sensor Networks in IoT Domains

Description

This book provides an essential overview of IoT, energy-efficient topology control protocols, motivation, and challenges for topology control for Wireless Sensor Networks, and the scope of the research in the domain of IoT. Further, it discusses the different design issues of topology control and energy models for IoT applications, different types of simulators with their advantages and disadvantages. It also discusses extensive simulation results and comparative analysis for various algorithms. The key point of this book is to present a solution to minimize energy and extend the lifetime of IoT networks using optimization methods to improve the performance. Features: Describes various facets necessary for energy optimization in IoT domain. Covers all aspects to achieve energy optimization using latest technologies and algorithms, in wireless sensor networks. Presents various IoT and Topology Control Methods and protocols, various network models, and model simulation using MATLAB®. Reviews methods and results of optimization with Simulation Hardware architecture leading to prolonged life of IoT networks. First time introduces bio-inspired algorithms in the IoT domain for performance optimization This book aims at Graduate Students, Researchers in Information Technology, Computer Science and Engineering, Electronics and Communication Engineering. Cover Half Title Title Page Copyright Page Contents Preface Author's Biography Abbreviations 1. Introduction and Background Study 1.1 IoT and WSN 1.1.1 Overview of WSN 1.1.2 How Does WSN Works? 1.1.2.1 Technology Sensor Node Power Source Microcontroller Sensor Transducer Transceiver Operating System 1.1.2.2 Gateways 1.1.2.3 Task Managers 1.1.2.4 Communication Architecture for WSNs WSN Communication Standards and Specifications ZigBee Bluetooth 6LoWPAN WSN Design Factors and Requirements Quality of Service Fault Tolerance Time of Data Delivery Energy Consumption Gathering Data Communication Architecture Homogeneous vs. Heterogeneous 1.1.3 Security Issues in WSN 1.2 IoT and Sensor Network Applications 1.2.1 Wide Space Applications 1.2.1.1 Smart Cities 1.2.1.2 Smart Environmental 1.2.1.3 Smart Agricultural 1.2.1.4 Defense Applications 1.2.2 Small Space Application 1.2.2.1 Operational Conditions Monitoring 1.2.2.2 Industrial Applications 1.2.2.3 Healthcare Applications 1.2.2.4 Intra-Vehicle Applications 1.3 OSI and IoT Layer Stack 1.3.1 Physical or Sensor Layer 1.3.2 Processing and Control Layer 1.3.3 Hardware Interface Layer 1.3.4 RF Layer 1.3.5 Session/Message Layer 1.3.6 User Experience Layer 1.3.7 Application Layer 1.4 Protocols in WSN and IoT 1.4.1 Routing Protocol for Low-Power and Lossy Networks 1.4.2 Cognitive RPL 1.4.2.1 Cognitive and Opportunistic RPL 1.4.3 Lightweight On-Demand Ad hoc Distance Vector Routing - Next Generation (LOADng) 1.4.4 Collection Tree Protocol 1.4.5 Channel-Aware Routing Protocol 1.4.6 E-CARP 1.5 Energy Consumption and Network Topology 1.6 Challenges for Energy Consumption in IoT Networks 1.6.1 Energy Consumption 1.6.2 Combination of IoT with Subsystems 1.6.3 User Privacy 1.6.4 Safety Challenge 1.6.5 IoT Standards 1.6.6 Architecture Design 1.7 Summary References 2. IoT and Topology Control: Methods and Protocol 2.1 Sensor Network Topologies 2.1.1 Star Network (Single Point-to-Multipoint) 2.1.2 Mesh Network Topology 2.1.3 Hybrid Star-Mesh Network Topology 2.2 IoT and Topology Control Methods 2.2.1 Powder Adjustment Approach 2.2.2 Powder Mode Approach 2.2.3 Clustering Approach 2.2.4 Hybrid Approach 2.3 Comparative Analysis: Topology Control Methods 2.3.1 Evaluations Based on the Network Lifetime Definitions 2.3.2 Evaluations Based on the Network Lifetime Definitions 2.3.3 Evaluations Based on the Network Lifetime Definitions 2.3.4 Evaluations based on the Network Lifetime Definitions 2.4 IoT and Topology Control Protocols 2.4.1 Link Efficiency-Based Topology Control 2.4.2 Improved Reliable and Energy Efficient Topology Control 2.4.3 Cellular Automata-Based Topology Control 2.4.4 Heterogeneous Topology Control Algorithm (HTC) 2.5 IoT and Routing Protocols 2.5.1 Routing Protocol for Low-Power and Lossy Networks (RPL) 2.5.1.1 What Is RPL? 2.5.1.2 RPL Network Topology 2.5.1.3 RPL Messages 2.5.1.4 Routing with RPL 2.5.2 Cognitive RPL (CORP) 2.5.3 Channel-Aware Routing Protocol (CARP) 2.6 Future Research Direction: Context-Aware Routing in IoT Networks 2.6.1 Routing in IoT 2.6.2 Need of Context-Awareness in IoT Routing 2.6.3 Context Needed for Routing 2.7 Summary References 3. Design Issues, Models, and Simulation Platforms 3.1 Topology Control Design issues 3.1.1 Taxonomy of Topology Issues 3.1.2 Topology Awareness Problem 3.1.3 Topology Control Problem 3.2 Network Models 3.2.1 Homogeneous Model 3.2.2 Wireless Propagation Model 3.2.3 Model of Long-Distance Path 3.2.4 Hop Model 3.2.5 Energy Model 3.3 Simulation Platforms 3.3.1 OMNeT++ 3.3.2 NS2 3.4 Simulation using MATLAB for IoT domain 3.4.1 The MATLAB System 3.4.2 MATLAB for IoT Domain 3.5 Future Research Direction: Heterogeneity of Network Technologies 3.5.1 Sensing Layer 3.5.2 Network Layer 3.5.3 Cloud Computing 3.5.4 Application Layer 3.5.4.1 Applications of Heterogeneous Network for IoT 3.5.5 Smart Industrial 3.5.6 Smart Agricultural 3.5.7 Smart Home 3.5.8 Intelligent Transportation System 3.5.9 Smart Healthcare 3.6 Summary References 4. Link Efficiency-Based Topology Control Algorithm for IoT Domain Application 4.1 Introduction 4.1.1 Received Signal Strength Indicator 4.1.2 Limitation of RSSI 4.2 Network Model 4.2.1 Definitions 4.2.2 Assumption 4.3 Improved Link Efficiency-Based Topology Control Algorithm 4.3.1 Proposed Algorithm: LEBTC 4.3.2 Mathematical Model 4.3.3 Flow Diagram 4.4 Implementations 4.4.1 RNG-Relative Neighborhood Graph 4.4.2 GG - Gabriel Graph 4.4.3 FETC and FETCD 4.5 Future Research Direction: Gateway Placement and Energy-Efficient Scheduling in IoT 4.5.1 Overview 4.5.2 Placement of Gateways 4.5.3 Task Model 4.5.4 Energy Consumption Model 4.5.5 Energy-Efficient Scheduling Algorithms 4.5.5.1 Global Algorithm 4.5.5.2 Local Algorithm 4.6 Summary References 5. Energy-Efficient Topology Control Algorithms for IoT Domain Applications 5.1 Introduction 5.1.1 Connected Dominating Set 5.1.1.1 Approach-I 5.1.1.2 Approach-II 5.1.2 Clustering Mechanisms 5.2 Network Model 5.3 Energy-Efficient Algorithm Based on Connected Dominating Set 5.3.1 Proposed Algorithm: iPOLY 5.3.2 Mathematical Model 5.3.3 Flow Diagrams 5.4 Implementations: POLY and iPOLY 5.5 Future Research Direction: IoT Reliability 5.5.1 Device Reliability 5.5.2 Network Reliability 5.5.3 System Reliability 5.5.4 Anomaly Detection 5.6 Summary References 6. Cellular Automata-Based Topology Control Algorithms for IoT Domain Applications 6.1 Introduction 6.1.1 Cellular Automata for Sensor Networks 6.1.2 Sensor Network Clustering 6.2 Cellular Automata-Based Topology Control Algorithms 6.2.1 Cellular Automata Weighted Margoles Neighborhood 6.2.2 Cellular Automata Weighted Moor Neighborhood 6.2.3 Cyclic Cellular Automata 6.2.3.1 Cellular Automata-Based Topology Control Algorithm 6.2.3.2 Mathematical Model 6.2.3.3 Greenberg-Hastings Model 6.2.3.4 Proposed CCA 6.2.3.5 Mathematical Analysis 6.2.3.6 Data Aggregation Model 6.2.3.7 Entropy Base Model 6.3 Future Research Direction: Cellular Automata for IoT Application 6.4 Summary References 7. Performance Optimization in IoT Networks 7.1 IoT Network Issues 7.1.1 Fault Tolerance 7.1.2 Security Enforcement 7.1.3 Handling Heterogeneity 7.1.4 Self-Configuration 7.1.5 Unintended Interference 7.1.6 Network Visibility 7.1.7 Restricted Access 7.2 Optimization Issues in IoT Networks 7.2.1 Data Aggregation 7.2.2 Routings in IoT Networks 7.2.3 Optimal Coverage 7.2.4 Sensor Localization 7.3 Optimization Levels in IoT 7.3.1 Device Level Optimization 7.3.2 Network Level Optimization 7.3.3 Application Level Optimization 7.4 Solutions for IoT Network Optimization 7.4.1 Network Routing 7.4.2 Energy Conservation 7.4.3 Congestion Control 7.4.4 Heterogeneity 7.4.5 Scalability 7.4.6 Network Reliability 7.4.7 Quality of Service 7.5 Summary References 8. Bio-Inspired Computing and IoT Networks 8.1 Bio-Inspired Approach 8.1.1 Bio-Inspired Computing 8.1.2 Bio-Inspired System 8.1.3 Bio-Inspired Engineering 8.2 Motivation for Bio-Inspired Computing 8.2.1 Self-Organization 8.2.2 Self-Adaptation 8.2.2.1 Flexible Infrastructure 8.2.2.2 Intelligence Analysis 8.2.2.3 Software Control Automation 8.2.3 Self-Healing Ability 8.3 Bio-Inspired Computing Approaches for Optimizations 8.3.1 Evolutionary Algorithms (EAs) 8.3.2 Artificial Neural Networks (ANNs) 8.3.3 Swarm Intelligence (SI) 8.3.4 Firefly Algorithm (FA) 8.3.5 Artificial Immune System (AIS) 8.3.6 Epidemic Spreading (ES) 8.4 Summary References 9. Blockchain and IoT Optimization 9.1 Blockchain Technology and IoT 9.1.1 Introduction to Blockchain 9.1.2 Blockchain Terminology 9.1.3 Blockchain Mechanism 9.1.4 Distributed P2P Networking 9.1.4.1 Steps in the Blockchain Transaction 9.1.4.2 Benefits of Using Blockchain 9.2 Blockchain Support for IoT Applications 9.2.1 Securing IoT Networks 9.2.2 Manufacturing Maintenance Support 9.2.3 Transparency in Supply Chain 9.2.4 In-Car Payment Model 9.2.5 Vehicle Insurance Model 9.2.6 Identity Authentication Using Self-Sovereign Identity (SSI) 9.3 Blockchain with IoT Networks Characteristics 9.3.1 Security 9.3.2 Scalability 9.3.3 Immutability and Auditing 9.3.4 Effectiveness and Efficiency 9.3.5 Traceability and Interoperability 9.3.6 Quality of Service 9.4 Energy Optimization and Blockchain Mechanism 9.4.1 Optimization Process 9.4.2 Resource Management Using Blockchain 9.5 Energy Optimization in Blockchain-Enabled IoT Networks 9.6 Summary References Index