Preface |
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xi | |
Author's Biography |
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xiii | |
Abbreviations |
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xv | |
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Chapter 1 Introduction and Background Study |
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1 | (18) |
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1 | (7) |
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1 | (1) |
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1.1.2 How Does WSN Works? |
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2 | (5) |
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1.1.3 Security Issues in WSN |
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7 | (1) |
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1.2 IoT and Sensor Network Applications |
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8 | (1) |
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1.2.1 Wide Space Applications |
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8 | (1) |
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1.2.2 Small Space Application |
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9 | (1) |
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1.3 OSI and IoT Layer Stack |
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9 | (2) |
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1.3.1 Physical or Sensor Layer |
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10 | (1) |
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1.3.2 Processing and Control Layer |
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10 | (1) |
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1.3.3 Hardware Interface Layer |
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11 | (1) |
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11 | (1) |
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1.3.5 Session/Message Layer |
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11 | (1) |
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1.3.6 User Experience Layer |
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11 | (1) |
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11 | (1) |
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1.4 Protocols in WSN and IoT |
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11 | (3) |
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1.4.1 Routing Protocol for Low-Power and Lossy Networks |
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12 | (1) |
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12 | (1) |
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1.4.3 Lightweight On-Demand AD hoc Distance Vector Routing - Next Generation (LOADng) |
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12 | (1) |
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1.4.4 Collection Tree Protocol |
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13 | (1) |
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1.4.5 Channel-Aware Routing Protocol |
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13 | (1) |
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14 | (1) |
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1.5 Energy Consumption and Network Topology |
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14 | (1) |
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1.6 Challenges for Energy Consumption in IoT Networks |
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14 | (2) |
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15 | (1) |
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1.6.2 Combination of IoT with Subsystems |
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15 | (1) |
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15 | (1) |
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15 | (1) |
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16 | (1) |
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1.6.6 Architecture Design |
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16 | (1) |
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16 | (3) |
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17 | (2) |
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Chapter 2 IoT and Topology Control: Methods and Protocol |
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19 | (50) |
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2.1 Sensor Network Topologies |
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19 | (2) |
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2.1.1 Star Network (Single Point-to-Multipoint) |
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19 | (1) |
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2.1.2 Mesh Network Topology |
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20 | (1) |
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2.1.3 Hybrid-Star-Mesh Network Topology |
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20 | (1) |
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2.2 IoT and Topology Control Methods |
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21 | (20) |
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2.2.1 Powder Adjustment Approach |
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23 | (3) |
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2.2.2 Powder Mode Approach |
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26 | (5) |
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2.2.3 Clustering Approach |
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31 | (5) |
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36 | (5) |
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2.3 Comparative Analysis: Topology Control Methods |
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41 | (12) |
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2.3.1 Evaluations Based on the Network Lifetime Definitions |
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44 | (3) |
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2.3.2 Evaluations Based on the Network Lifetime Definitions |
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47 | (2) |
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2.3.3 Evaluations Based on the Network Lifetime Definitions |
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49 | (2) |
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2.3.4 Evaluations Based on the Network Lifetime Definitions |
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51 | (2) |
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2.4 IoT and Topology Control Protocols |
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53 | (2) |
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2.4.1 Link Efficiency-Based Topology Control |
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53 | (1) |
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2.4.2 Improved Reliable and Energy Efficient Topology Control |
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54 | (1) |
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2.4.3 Cellular Automata-Based Topology Control |
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54 | (1) |
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2.4.4 Heterogeneous Topology Control Algorithm (HTC) |
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54 | (1) |
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2.5 IoT and Routing Protocols |
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55 | (5) |
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2.5.1 Routing Protocol for Low-Power and Lossy Networks (RPL) |
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55 | (4) |
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2.5.2 Cognitive RPL (CORP) |
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59 | (1) |
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2.5.3 Channel-Aware Routing Protocol (CARP) |
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60 | (1) |
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2.6 Future Research Direction: Context-Aware Routing in IoT Networks |
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60 | (4) |
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60 | (1) |
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2.6.2 Need of Context-Awareness in IoT Routing |
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61 | (1) |
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2.6.3 Context Needed for Routing |
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61 | (3) |
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64 | (5) |
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64 | (5) |
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Chapter 3 Design Issues, Models, and Simulation Platforms |
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69 | (24) |
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3.1 Topology Control Design Issues |
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69 | (7) |
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3.1.1 Taxonomy of Topology Issues |
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70 | (1) |
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3.1.2 Topology Awareness Problem |
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71 | (2) |
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3.1.3 Topology Control Problem |
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73 | (3) |
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76 | (3) |
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76 | (1) |
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3.2.2 Wireless Propagation Model |
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77 | (1) |
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3.2.3 Model of Long-Distance Path |
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77 | (1) |
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78 | (1) |
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78 | (1) |
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79 | (2) |
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79 | (1) |
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80 | (1) |
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3.4 Simulation Using MATLAB for IoT Domain |
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81 | (1) |
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81 | (1) |
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3.4.2 MATLAB for IoT Domain |
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82 | (1) |
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3.5 Future Research Direction: Heterogeneity of Network Technologies |
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82 | (6) |
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83 | (1) |
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84 | (1) |
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84 | (1) |
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84 | (1) |
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85 | (1) |
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86 | (1) |
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86 | (1) |
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3.5.8 Intelligent Transportation System |
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87 | (1) |
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87 | (1) |
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88 | (5) |
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88 | (5) |
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Chapter 4 Link Efficiency-Based Topology Control Algorithm for IoT Domain Application |
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93 | (28) |
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93 | (1) |
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4.1.1 Received Signal Strength Indicator |
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93 | (1) |
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94 | (1) |
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94 | (2) |
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95 | (1) |
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96 | (1) |
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4.3 Improved Link Efficiency-Based Topology Control Algorithm |
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96 | (3) |
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4.3.1 Proposed Algorithm: LEBTC |
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97 | (1) |
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98 | (1) |
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99 | (1) |
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99 | (11) |
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4.4.1 RNG-Relative Neighborhood Graph |
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99 | (1) |
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99 | (1) |
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99 | (11) |
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4.5 Future Research Direction: Gateway Placement and Energy-Efficient Scheduling in IoT |
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110 | (8) |
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110 | (5) |
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4.5.2 Placement of Gateways |
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115 | (1) |
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116 | (1) |
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4.5.4 Energy Consumption Model |
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116 | (1) |
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4.5.5 Energy-Efficient Scheduling Algorithms |
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116 | (2) |
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118 | (3) |
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119 | (2) |
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Chapter 5 Energy-Efficient Topology Control Algorithms for IoT Domain Applications |
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121 | (16) |
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121 | (4) |
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5.1.1 Connected Dominating Set |
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121 | (4) |
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5.1.2 Clustering Mechanisms |
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125 | (1) |
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125 | (1) |
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5.3 Energy-Efficient Algorithm Based on Connected Dominating Set |
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126 | (3) |
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5.3.1 Proposed Algorithm: iPOLY |
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127 | (1) |
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127 | (2) |
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129 | (1) |
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5.4 Implementations: POLY and iPOLY |
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129 | (1) |
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5.5 Future Research Direction: IoT Reliability |
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130 | (4) |
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130 | (3) |
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5.5.2 Network Reliability |
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133 | (1) |
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133 | (1) |
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134 | (1) |
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134 | (3) |
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134 | (3) |
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Chapter 6 Cellular Automata-Based Topology Control Algorithms for IoT Domain Applications |
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137 | (18) |
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137 | (3) |
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6.1.1 Cellular Automata for Sensor Networks |
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139 | (1) |
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6.1.2 Sensor Network Clustering |
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140 | (1) |
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6.2 Cellular Automata-Based Topology Control Algorithms |
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140 | (12) |
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6.2.1 Cellular Automata Weighted Margoles Neighborhood |
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140 | (1) |
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6.2.2 Cellular Automata Weighted Moor Neighborhood |
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141 | (2) |
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6.2.3 Cyclic Cellular Automata |
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143 | (9) |
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6.3 Future Research Direction: Cellular Automata for IoT Application |
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152 | (1) |
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153 | (2) |
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153 | (2) |
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Chapter 7 Performance Optimization in IoT Networks |
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155 | (26) |
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155 | (5) |
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155 | (1) |
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7.1.2 Security Enforcement |
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156 | (1) |
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7.1.3 Handling Heterogeneity |
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157 | (1) |
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158 | (1) |
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7.1.5 Unintended Interference |
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158 | (2) |
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160 | (1) |
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160 | (1) |
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7.2 Optimization Issues in IoT Networks |
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160 | (6) |
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162 | (1) |
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7.2.2 Routings in IoT Networks |
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163 | (1) |
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164 | (1) |
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7.2.4 Sensor Localization |
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165 | (1) |
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7.3 Optimization Levels in IoT |
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166 | (5) |
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7.3.1 Device Level Optimizationn |
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167 | (1) |
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7.3.2 Network Level Optimization |
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168 | (2) |
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7.3.3 Application Level Optimization |
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170 | (1) |
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7.4 Solutions for IoT Network Optimization |
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171 | (7) |
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172 | (1) |
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7.4.2 Energy Conservation |
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172 | (2) |
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174 | (1) |
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174 | (1) |
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175 | (1) |
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7.4.6 Network Reliability |
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176 | (1) |
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177 | (1) |
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178 | (3) |
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179 | (2) |
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Chapter 8 Bio-Inspired Computing and IoT Networks |
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181 | (24) |
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8.1 Bio-Inspired Approach |
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181 | (3) |
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8.1.1 Bio-Inspired Computing |
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181 | (1) |
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8.1.2 Bio-Inspired System |
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181 | (2) |
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8.1.3 Bio-Inspired Engineering |
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183 | (1) |
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8.2 Motivation for Bio-Inspired Computing |
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184 | (4) |
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184 | (1) |
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185 | (1) |
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8.2.3 Self-Healing Ability |
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186 | (2) |
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8.3 Bio-Inspired Computing Approaches for Optimizations |
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188 | (15) |
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8.3.1 Evolutionary Algorithms (EAs) |
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189 | (4) |
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8.3.2 Artificial Neural Networks (ANNs) |
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193 | (3) |
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8.3.3 Swarm Intelligence (SI) |
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196 | (2) |
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8.3.4 Firefly Algorithm (FA) |
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198 | (1) |
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8.3.5 Artificial Immune System (AIS) |
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199 | (2) |
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8.3.6 Epidemic Spreading (ES) |
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201 | (2) |
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203 | (2) |
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204 | (1) |
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Chapter 9 Blockchain and IoT Optimization |
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205 | (20) |
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9.1 Blockchain Technology and IoT |
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205 | (4) |
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9.1.1 Introduction to Blockchain |
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205 | (1) |
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9.1.2 Blockchain Terminology |
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205 | (1) |
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9.1.3 Blockchain Mechanism |
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206 | (2) |
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9.1.4 Distributed P2P Networking |
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208 | (1) |
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9.2 Blockchain Support for IoT Applications |
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209 | (5) |
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9.2.1 Securing IoT Networks |
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209 | (1) |
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9.2.2 Manufacturing Maintenance Support |
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210 | (2) |
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9.2.3 Transparency in Supply Chain |
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212 | (1) |
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9.2.4 In-Car Payment Model |
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212 | (1) |
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9.2.5 Vehicle Insurance Model |
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213 | (1) |
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9.2.6 Identity Authentication Using Self-Sovereign Identity (SSI) |
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213 | (1) |
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9.3 Blockchain with IoT Networks Characteristics |
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214 | (6) |
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215 | (1) |
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215 | (2) |
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9.3.3 Immutability and Auditing |
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217 | (1) |
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9.3.4 Effectiveness and Efficiency |
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217 | (2) |
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9.3.5 Traceability and Interoperability |
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219 | (1) |
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220 | (1) |
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9.4 Energy Optimization and Blockchain Mechanism |
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220 | (2) |
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9.4.1 Optimization Process |
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221 | (1) |
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9.4.2 Resource Management Using Blockchain |
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221 | (1) |
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9.5 Energy Optimization in Blockchain-Enabled IoT Networks |
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222 | (1) |
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223 | (2) |
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223 | (2) |
Index |
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225 | |