thesis

1. ix
Table of Contents
Sl.No Title
Page
No.
Title Page i
Abstract ii
Table of contents iv
List of Figures ix
List of Tables xii
List of Acronyms xiii
1 CHAPTER 1: Introduction 1
1.1 Introduction: WSN 2
1.2 Applications of WSN 3
1.2.1Environmental/Habitat Monitoring 3
1.2.2 Health Care Applications 4
1.2.3 Military Applications 5
1.2.4 Industry object tracking 6
1.2.5 Security and Surveillance 6
1.2.6 Defence Applications 7
1.2.7 Home Automation 7
1.2.8 Heavy Industrial Monitoring 7
1.3 Wireless Sensor Node Architecture 8
1.4 Coverage in WSN 10
1.4.1 Dynamic Coverage 11
1.4.1.1 Based on virtual force 12
1.4.1.2 Graph Based 12
1.4.1.3 Event Detection 12
1.4.2 Static Coverage 14
1.4.2.1 Efficient coverage area 14
1.4.2.2 Path Coverage 15
1.4.2.3 K-Coverage 16
1.5 Connectivity in WSN 17
1.6 Research Motivation 18
1.6.1 Connectivity in Sparse WSN 18

2. x
1.6.2 Connectivity in Dense WSN 18
1.6.3 Coverage problems in WSN 19
1.7 Organization of Thesis 20
2 CHAPTER 2: Literature Review 21
2.1 Introduction 22
2.2 Clustering Methods 23
2.3 Coverage Optimization Algorithms 25
2.4 Scheduling algorithms 28
2.5 Energy-efficient algorithms 31
2.6 Coverage preserving protocols 33
2.7 Connectivity Maintenance Protocols 36
3 CHAPTER 3: Boolean Directional Sensor Orientation
Solution for K-Coverage
39
3.1 Introduction 40
3.2 Motivation 41
3.3 Optimization 42
3.3.1 Models 42
3.3.2 Optimizer/Algorithm 42
3.3.3 Evaluator or Simulator 43
3.4 WSN Optimization 43
3.4.1 WSN Optimization Problems 43
3.4.2 WSN Optimization Solvers 43
3.5 Coverage and k-Coverage Optimization in WSN 44
3.5.1 Coverage in WSNs 44
3.5.2 K-coverage Calculation 45
3.5.3 Area Coverage calculation 45
3.5.4 K-Coverage Problem in WSN 46
3.5.5 K-Connected Target Coverage Issue 47
3.5.6 k-degree coverage algorithm based on
optimization nodes deployment
48
3.5.7 Framework for the Optimal k-Coverage
Deployment Patterns
49

3. xi
3.5.8 Solving K-Coverage Problem Using Improved
Harmony Search
50
3.5.9 Optimizing K-coverage of mobile WSNs 51
3.5.10 K-Coverage Model based on Genetic
Algorithm to extend WSN lifetime
51
3.6 Proposed Approach: For K-Coverage issue the
Boolean Directional Sensor Orientation Solution
51
3.6.1 Directional Sensors model and variables 51
3.6.2 Coverage probability estimation (CPE) of
directional sensor
54
3.6.3 Linear formulation for coverage 55
3.7 Significance of Optimization in WSNs 56
3.7.1 Protocol Architectural and Its Significance in
WSNs
57
3.7.2 Optimization Solutions for Conventional
Protocol Architecture
58
3.8 Result and Discussion 59
4
CHAPTER 4: Hybrid Gravitational Search Algorithm
based model for optimizing coverage and connectivity
62
4.1 Introduction 63
4.2 Key points of k-coverage problem 65
4.3 System Model 68
4.4 Problem Statement 68
4.5 Clustering 68
4.5.1 Formulation of MILP 69
4.5.2 Fitness function for k-coverage problem 70
4.6 Proposed HGSA based Approach 72
4.7 Experiments and results 80
5
CHAPTER 5: Efficient Energy and Position Aware
Routing Protocol for WSN
92
5.1 Introduction 93
5.2 Routing Protocol in WSNs 95
5.3 System model 96

4. xii
5.3.1 Scenario Description 96
5.3.2 Energy Model 97
5.3.3 Communication Stack 98
5.4 Problem formulation 98
5.4.1 Blind forwarding and Data inaccessibility 100
5.5 Proposed Work 101
5.5.1 Initial assumption 101
5.5.2 Working Mechanism 102
5.5.2.1 Node-to-sink distance calculation 103
5.5.2.2 Advertising Phase 104
5.5.2.3 Request Phase 104
5.5.2.4 Data Transmission Phase 106
5.6 Complexity Analysis 107
5.7 Performance analysis 107
5.7.1 Result discussion 108
5.7.2 Statistical validation: Analysis of variance
(ANOVA)
110
6
Chapter 6: Hybrid Neural Network Based Energy
Efficient Routing Strategy
120
6.1 Introduction 121
6.2 Hybrid Neural Network based Energy efficient
Routing
124
6.2.1 System Model 125
6.2.2 Energy Model 126
6.3 Cluster Formation: Mean shift algorithm 126
6.4 CH selection: BES Algorithm 128
6.4.1 Select stage 129
6.4.2 Search stage 129
6.4.3 Swooping stage 130
6.5 Optimized HNN based routing using GTA 134
6.6 Simulation Results and Discussion 139
7 CHAPTER 7: Conclusion and Future Scope 150
8 CHAPTER 8: References 153