Energy efficient routing protocols

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Table of contents

1 General Introduction 
1.1 Background and motivations
1.2 Main contributions
1.3 Manuscript organization
I StateoftheArt 
2 EnergyEfficientTechniques inWSNs 
2.1 Introduction
2.2 Network lifetime definition
2.3 Taxonomy of energy efficient techniques
2.3.1 Reasons of energy waste
2.3.2 Classification of energy efficient techniques
2.4 Energy efficient routing protocols
2.5 Duty cycling
2.6 Conclusion
3 Multi channel Assignment Protocols inWSNs 
3.1 Introduction
3.2 Issues in multichannel communications and specificities of WSNs
3.3 Particularities of channel assignment strategies in WSNs
3.3.1 Classification of mesh channel assignment strategies
3.3.2 Applicability of mesh channel assignment strategies
3.4 Network architecture for multichannel communication in WSN
3.4.1 A two-level architecture
3.4.2 A three-level architecture
3.4.3 A three-level mesh architecture
3.5 Network model for a multichannel WSN
3.5.1 Radio propagation
3.5.2 Interferences
3.5.3 Connectivity
3.6 Classification of existing multichannel assignment protocols in WSNs
3.6.1 Categories of channel assignment method
3.6.2 Channel selection policy
3.6.3 Channel assignment methods
3.6.4 Discussion
3.7 Cross-layer design for multichannel allocation and routing
3.8 Taxonomy proposed
3.9 Conclusion
II Joint Multipath Routing and Scheduling in Multichannel WSNs 
4 Lower Bounds for Convergecast: Theoretical Study 
4.1 Introduction and motivations
4.2 Network models and assumptions
4.2.1 System model
4.2.2 Definitions
4.2.3 Assumptions
4.2.4 Modeling interferences for data gathering
4.2.5 Notations
4.3 Theoretical bounds for homogeneous traffic
4.3.1 Linear networks
4.3.2 Tree networks
4.3.3 Optimal schedule
4.4 Theoretical bounds for heterogeneous traffic
4.4.1 Without immediate acknowledgment
4.4.2 With immediate acknowledgment
4.5 Conclusion
5 MODESA: an Optimized Multichannel Slot Assignment for Raw Converge- cast in WSNs 
5.1 Introduction
5.2 State of the art
5.3 Multichannel slot assignment problem
5.3.1 Formalization of the problem
5.3.2 Illustrative examples
5.4 MODESA: Multichannel Optimized DElay time Slot Assignment
5.4.1 Principles
5.4.2 The MODESA algorithm
5.4.3 Optimality of MODESA for homogeneous traffic
5.5 Performance evaluation of MODESA
5.5.1 MODESA with homogeneous traffic
5.5.2 MODESA with heterogeneous traffic
]5.5.3 Impact of additional links
5.6 MODESA improvement
5.6.1 Channel allocation strategy
5.6.2 Multipath transmission scheduling
5.6.3 Different topologies on different channels
5.7 Conclusion
6 MUSIKA: a MUlti-SInk Slot Assignment for Convergecast in Multichannel WSNs 
6.1 Introduction
6.2 State of the art
6.3 Network model and problem formalization
6.3.1 Network model
6.3.2 Multi-sink multichannel convergecast problem formulation
6.4 MUSIKA: MUlti-SInK slot Assignment
6.4.1 Principles
6.4.2 Algorithm
6.5 Illustrative example
6.6 Performance evaluation
6.7 Conclusion
III Adaptivity and Scalability of Joint Time Slot and Channel Assignment 
7 An Adaptive Strategy for an Optimized Collision-Free Slot Assignment in Multichannel Wireless Sensor Networks 
7.1 Introduction
7.2 State of the art
7.3 Adaptive multichannel slot assignment
7.3.1 Definitions
7.3.2 Assumptions
7.3.3 Network model
7.3.4 Theoretical bounds on the number of extra slots for a raw data convergecast
7.3.5 AMSA: Proposed solution
7.3.6 Illustrative example
7.4 Performance evaluation
7.4.1 Retransmission oriented experiments
7.4.2 Temporary change in the application needs-oriented experiments
7.5 Conclusion
8 A Distributed Joint Channel and Time Slot Assignment for Convergecast in Multichannel WSNs 
8.1 Introduction
8.2 State of the art
8.3 WAVE: a distributed time slot and channel assignment for convergecast in WSNs
8.3.1 WAVE in centralized mode
8.3.2 WAVE in distributed mode
8.3.3 Properties
8.3.4 Equivalence of the two modes of WAVE
8.3.5 Message complexity in the two modes of WAVE
8.4 DiSCA: an optimized version of WAVE
8.4.1 Principles
8.4.2 DiSCA distributed algorithm
8.5 Comparative performance evaluation of WAVE and DiSCA
8.5.1 Homogeneous traffic
8.5.2 Heterogeneous traffic
8.6 Conclusion
9 Conclusion and Perspectives 
9.1 Synthesis
9.2 Perspectives
A List of Publications 
B Résumé 
B.1 Contexte et motivations
B.2 Allocation conjointe de slot et canaux dans les RCsF
B.2.1 Bornes théoriques
B.3 MODESA: algorithme optimisé pour l’allocation conjointe de slots temporels et canaux
B.3.1 Optimalité de MODESA
B.3.2 Evaluation de performances
B.4 MUSIKA: algorithme d’allocation conjointe de slots et de canaux pour les RCsF multicanaux multi-puits
B.5 Adaptabilité et passage à l’échelle pour l’allocation conjointe des slots temporels et canaux
B.5.1 Stratégie adaptative pour l’allocation conjointe de slot temporel et canaux
B.6 Allocation distribuée conjointe de slots et canaux pour les applications collecte de données
B.6.1 WAVE: algorithme distribué d’allocation conjointe de slots temporels
et canaux pour les applications de collecte de données
B.6.2 DiSCA: Une version optimisée de WAVE
B.6.3 Evaluation comparative de WAVE et DiSCA
B.7 Conclusion et perspectives
Bibliography