Estimating Self-Sustainability in Peer-to-Peer Swarming Systems

TL;DR

This paper introduces a new metric called swarm self-sustainability to measure how often peer-to-peer swarms can independently hold all content blocks, analyzing factors like content popularity, user capacity, and file size.

Contribution

It proposes a novel metric and a model to evaluate and compute the self-sustainability of swarms, validated through simulations and closed-form expressions.

Findings

Self-sustainability decreases with lower content popularity.

Higher user service capacity improves swarm self-sustainability.

The model accurately predicts self-sustainability compared to simulations.

Abstract

Peer-to-peer swarming is one of the \emph{de facto} solutions for distributed content dissemination in today's Internet. By leveraging resources provided by clients, swarming systems reduce the load on and costs to publishers. However, there is a limit to how much cost savings can be gained from swarming; for example, for unpopular content peers will always depend on the publisher in order to complete their downloads. In this paper, we investigate this dependence. For this purpose, we propose a new metric, namely \emph{swarm self-sustainability}. A swarm is referred to as self-sustaining if all its blocks are collectively held by peers; the self-sustainability of a swarm is the fraction of time in which the swarm is self-sustaining. We pose the following question: how does the self-sustainability of a swarm vary as a function of content popularity, the service capacity of the users, and the size of the file? We present a model to answer the posed question. We then propose efficient solution methods to compute self-sustainability. The accuracy of our estimates is validated against simulation. Finally, we also provide closed-form expressions for the fraction of time that a given number of blocks is collectively held by peers.