DTN characterization and end-to-end connectivity usage

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Table of contents

1 Introduction 
1.1 Opportunistic Networks: Characteristics and Challenges
1.2 Motivating Example
1.3 Problem Statement
1.4 Contributions of this Thesis
2 Related Work and Datasets 
2.1 Related Work
2.1.1 Contact and intercontact vision
2.1.2 DTN characterization and end-to-end connectivity usage
2.1.3 Routing techniques
2.1.4 Mobility models
2.1.5 Prediction in DTNs
2.2 Datasets
2.2.1 Connectivity assumptions
2.2.2 Real-world datasets
2.2.3 Synthetic datasets
3 Uncovering Vicinity Properties of Intercontacts inDTNs 
3.1 The Binary Assertion Issue
3.2 The Notion of Vicinity
3.2.1 Vicinity definition for opportunistic networks
3.2.2 Missed transmission possibilities with binary assertion
3.2.3 Pairwise behavior variability
3.3 Temporal !-vicinity Characterization
3.3.1 !-intercontact distributions
3.3.2 !-contact distributions
3.4 Inner Topological Characterization
3.4.1 The seat of !-vicinities: connected components
3.4.2 !-vicinity ego density Di!
3.4.3 A rule of thumb for card(Vi!
3.5 The Strength of Vicinity Annexation
3.5.1 Threshold optimization
3.5.2 Loss and delays
3.5.3 Overheads
3.6 Recommandations
3.7 Conclusion
4 Digging into the Vicinity Dynamics ofMobile Opportunistic Networks 
4.1 Why Vicinity Dynamics?
4.2 Vicinity Package Introduction
4.3 The Asynchronous Vicinity Motion Framework
4.3.1 Timeline generation
4.3.2 Vicinity analysis
4.4 Asynchronous Vicinity Motion: Analyses and Patterns
4.4.1 Short and extended chains
4.4.2 Max-min distance division
4.4.3 Vicinity chains distributions
4.4.4 Vicinity patterns
4.4.5 Asynchronous vicinity motion take-aways
4.5 TiGeR: Synthetic Timeline Generator
4.5.1 Motivation
4.5.2 Generation processes
4.5.3 Evaluation
4.6 Observations
4.7 Conclusion
5 PredictingVicinityDynamics 
5.1 Problem Statement
5.2 Vicinity Motion-based Markovian Heuristic
5.2.1 Synchronous vicinity motion (SVM)
5.2.2 Heuristic
5.2.3 Implementation
5.3 Methodology
5.4 Complete Knowledge Heuristic Evaluation
5.4.1 AVM-full
5.4.2 SVM-full
5.5 Partial Knowledge Heuristic Evaluation
5.5.1 AVM-half
5.5.2 SVM-half
5.6 Conclusion
6 Conclusion & Perspectives 
6.1 Summary of Contributions in this Thesis
6.2 General Remarks
6.3 Perspectives on Research Directions
A List of Publications
List of Figures
List of Tables
Bibliography