Coverage and connectivity issues in WSNs

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Table of contents

Acknowledgement
Abstract
1 General Introduction
1.1 Context and motivation
1.2 Main contributions
1.3 Manuscript organization
Part I : State of the art
2 Coverage and connectivity issues in WSNs
2.1 Introduction
2.2 Denition of coverage and connectivity problems in WSNs
2.2.1 Coverage problems
2.2.2 Connectivity problems
2.3 Representative use cases
2.4 Coverage and connectivity problems with regard to R and r
2.5 Coverage and connectivity with regard to regular optimal deployment .
2.6 Conclusion
3 Deployment algorithms in WSNs
3.1 Introduction
3.2 Analysis of the criteria of deployment algorithms
3.2.1 Factors impacting the deployment
3.2.2 Common assumptions and models
3.2.3 Criteria for performance evaluation
3.3 Area coverage and connectivity algorithms
3.3.1 Full coverage
3.3.2 Partial coverage
3.3.3 Intermittent connectivity
3.3.4 Summary
3.4 Barrier coverage and connectivity algorithms
3.4.1 Full barrier coverage
3.4.2 Partial barrier coverage
3.4.3 Summary
3.5 Point coverage and connectivity algorithms
3.5.1 Static PoI
3.5.2 Mobile PoIs
3.5.3 Summary
3.6 Node activity scheduling with regard to coverage
3.6.1 Node activity scheduling based on message exchanges between neighbors
3.6.2 Node activity scheduling based on implicit coordination
3.7 Guidelines for selecting a deployment algorithm
3.8 Conclusion
Part II : Models and theoretical computation for an optimized deployment in 2D and 3D
4 Models for an optimized deployment
4.1 Introduction
4.2 Models for 2D deployment
4.2.1 Sensing range and communication range in 2D
4.2.2 The area considered and obstacles in 2D
4.3 Models for 3D deployment
4.3.1 Sensing range and communication range in 3D
4.3.2 The area considered and obstacles in 3D
4.4 Conclusion
5 Theoretical computation of an optimized deployment in 2D and 3D
5.1 Introduction
5.2 Theoretical computation of an optimal 2D deployment
5.2.1 Target distance in the optimal deployment
5.2.2 Optimal number of sensors to cover a given area
5.2.3 Computation of the eective distance
5.3 Theoretical computation of an optimized 3D deployment
5.3.1 Best polyhedron tessellation for 3D space
5.3.2 Optimized number of nodes to cover 3D space
5.4 Conclusion
Part III : Autonomous deployment
6 Virtual forces based algorithms
6.1 Introduction
6.2 DVFA: Distributed Virtual Forces Algorithm
6.2.1 DVFA principles
6.2.2 Performance evaluation
6.2.3 Summary
6.3 How to cope with node oscillations
6.3.1 ADVFA: Adaptive Distributed Virtual Forces Algorithm
6.3.2 GDVFA: Grid Distributed Virtual Forces Algorithm
6.3.3 Summary
6.4 How to cope with the presence of known or unknown obstacles
6.4.1 Obstacles and deployment algorithms
6.4.2 OA-DVFA: Obstacles Avoidance Distributed Virtual Forces Algorithm
6.4.3 Summary
6.5 How to use virtual forces in 3D
6.5.1 3D-DVFA: 3D Distributed Virtual Forces Algorithm
6.6 Conclusion
Part IV : Assisted deployment
7 Optimized deployment in the presence of obstacles
7.1 Introduction
7.2 First problem: full area coverage and connectivity
7.2.1 Optimized deployment in an irregular area
7.2.2 Optimized deployment in an irregular area with opaque obstacles .
7.2.3 Summary
7.3 Second problem: PoI coverage and connectivity
7.3.1 Related work
7.3.2 Denition of relay node placement problems
7.3.3 Solution for Relay Node Placement: RNP
7.3.4 Solution for Fault-tolerant RNP: FT-RNP
7.3.5 Solution for Constrained fault-tolerant RNP: CFT-RNP
7.3.6 Summary
7.4 Conclusion
8 Optimization of Robot Trajectories
8.1 Introduction
8.2 Related work
8.3 Two-robot assisted deployment: based on a game theory approach
8.3.1 Assumptions and denitions
8.3.2 Deployment duration and obstacles
8.3.3 Problem formalization
8.3.4 Problem resolution
8.4 Multi-robot assisted deployment: based on a multi-objective optimization approach
8.4.1 Problem formalization
8.4.2 NSGA-II based approach for MRDS optimization
8.4.3 Hybrid algorithm for the MRDS problem
8.4.4 Problem resolution
8.5 Conclusion
Part V : Discussion and Conclusion
9 Conclusion and perspectives
9.1 Conclusion
9.1.1 Synthesis
9.1.2 Application to the Cluster Connexion project
9.2 Perspectives and Discussion
9.2.1 More realistic models
9.2.2 From 2D toward 3D
9.2.3 Implementation on real robots
9.2.4 Use of our algorithms to collect data
List of Publications
A A Robot Trajectory Optimization
A.1 Introduction and motivation
A.2 Formalization of the RDS problem
A.3 Proposed algorithms
A.3.1 The exact solution
A.3.2 2-Opt algorithm
A.3.3 Genetic algorithm
A.3.4 Hybrid algorithm
A.4 Comparative evaluation
A.5 Discussion
A.5.1 Obstacles
A.5.2 Capacity constraint
A.5.3 Energy constraint
A.6 Conclusion
B Résumé
B.1 Introduction
B.1.1 Les problèmes de couverture et de connectivité
B.1.2 Les problèmes de connectivité
B.2 Contraintes, hypothèses et modèles théoriques pour le déploiement en 2D et 3D
B.3 Déploiement autonome
B.4 Déploiement assisté par robots mobiles
B.4.1 Calcul du déploiement optimisé
B.4.2 Optimisation des trajectoires des robots
B.5 Conclusion et perspectives
B.5.1 Synthèse
B.5.2 Perpectives
Bibliography