Centrality map calculation

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Table of contents

1 Introduction 
1.1 Problem statement and positioning
1.2 Contributions and thesis outline
2 Centrality estimation through spatial positioning 
2.1 Intuition
2.2 Related work
2.3 Our proposal: Geo-centrality
2.4 Applying centrality maps to vehicular networks
2.5 Results
2.6 Influence of parameters
2.7 Use case: Closeness as an epidemic propagation tool
2.8 Conclusion and future work
3 Characterization of D2D throughput through empirical validation
3.1 Related work
3.2 Stock Android High-Speed D2D APIs
3.3 Experimental procedure
3.4 Devices testing
3.5 RSSI for goodput estimation
3.6 Goodput estimation according to distance
3.7 Conclusion and future work
4 Computing realistic and adaptive capacity of D2D contacts 
4.1 Related work
4.2 Definitions and problem formulation
4.3 Empirical reference link characterization
4.4 Fixed vs. adaptive contact characterization
4.5 Contact network capacity computation tool
4.6 Conclusion
5 Conclusion and perspectives 
5.1 Summary and takeaways
5.2 Perspectives
References 
Appendix A Realistic contact computation library: OpportunistiKapacity
A.1 Basic run using wrapper
A.2 Supported traces
A.3 Mobility trace
A.4 Module and classes