Reducing Free Riding in Peer-to-Peer Systems with Supervised Teaming

Abstract

Peer-to-peer technology has produced thriving communities in which peers contribute bandwidth to each other. However, when free riding occurs, these communities will not be able to sustain themselves without incentives to enforce this contribution. This thesis presents Supervised Teaming, a peer-to-peer transfer protocol that gives uploading peers, called supervisors, control over a team of downloading peers, called team members. The team members are given an incentive to transfer data among each other, effectively reducing the upload cost of the supervisors to one piece of data while still duplicating this piece to every team member. Using transport efficiency, time efficiency, and sharing ratio as performance metrics, we prove that Supervised Teaming performs equally to BitTorrent under best-case scenarios and several factors better, depending on the chosen team size, under flash crowds and free riding scenarios. Furthermore, we have implemented a peer-to-peer client that can use both the BitTorrent protocol and a simplified version of the Supervised Teaming protocol. The experiments we have performed with this client verify that Supervised Teaming performs as expected.