Stratification in P2P Networks - Application to BitTorrent

TL;DR

This paper models decentralized P2P networks using stable matching theory, analyzing convergence, stratification, and applying insights to optimize BitTorrent's Tit-for-Tat policy.

Contribution

It introduces a stable matching-based model for P2P networks, proving convergence and stratification properties, and applies it to improve BitTorrent strategies.

Findings

Unique stable solution exists for the model

System converges towards the stable solution

Insights for optimizing BitTorrent peer strategies

Abstract

We introduce a model for decentralized networks with collaborating peers. The model is based on the stable matching theory which is applied to systems with a global ranking utility function. We consider the dynamics of peers searching for efficient collaborators and we prove that a unique stable solution exists. We prove that the system converges towards the stable solution and analyze its speed of convergence. We also study the stratification properties of the model, both when all collaborations are possible and for random possible collaborations. We present the corresponding fluid limit on the choice of collaborators in the random case. As a practical example, we study the BitTorrent Tit-for-Tat policy. For this system, our model provides an interesting insight on peer download rates and a possible way to optimize peer strategy.