outline.md

1. Introduction

   • What is a Darknet, effects, features for its users
   • Arising problems from its characteristics
   • name the analysing methods (and 1 sentence explanation)
     • analytic
     • simulation
     • emulation
     • testbed (and/or measurement in real world networks)
   • Advantages of event based large scale simulation and in generell analysability of darknets

2. Darknets

   • Detailed explanation of characteristics
     • (short) what is a P2P overlay; how they differ
     • only connected to people one trusts
     • no (concrete) topology information leakage
   • Implications of those characteristics
   • Survey of existing darknets
     • (historical perspective ?)
     • mainly grouped/sorted by used test/analysing methods
     • implemented/pure theoretical work
     • (turtle/wase,gnugnet,oneswarm,freenet,mcon,x-vine, (eventuell prefix embedding von Andreas Höfer)
   • Recap and explain used metrices and analysis methods

3. My Model

   • Why we chose the simulation based approach
   • Node based with fixed neighbor set
   • Churn model extension with bootstrapping & offline detection
   • Selection of OMNet++
   • Implementaion of the Model
     • two simple example routing models
     • randomwalk
       • with n-degree fanout
       • loopdetection
     • flooding

4. Simulation and Analysis

   • Simulation environment
   • Used metrices
     • (average/max) path length
     • sent message count
     • faild routings / requests OR droped packages
   • Q: Scalability of the model/framework
     • Used RAM; RAM RAM and moar RAM
   • Q: Impact of fanout degre at randomwalk on found pathlength
     • comparison to flooding which finds shortest path
   • Q: Probability of path failure on return for churn model

5. Conclusion and Future Work

   • Everything is epic, but.. ;)
   • Implement tested darknets and compare to their tests
   • Implement untested/new nets and improve routing parameters
     • or even decide if algorythm is pratical usefull or not