Optimal Content Placement for Peer-to-Peer Video-on-Demand Systems

TL;DR

This paper investigates optimal content placement strategies in peer-to-peer video-on-demand systems to maximize bandwidth utilization, analyzing different scaling scenarios and proposing strategies based on a random graph model.

Contribution

It introduces asymptotically optimal content placement strategies for P2P systems under various scaling regimes, including large catalog scenarios.

Findings

Optimal strategies depend on system scaling and catalog size.

Storage space per peer must grow unboundedly for maximum bandwidth utilization.

A specific random graph model guides the proposed content placement policy.

Abstract

In this paper, we address the problem of content placement in peer-to-peer systems, with the objective of maximizing the utilization of peers' uplink bandwidth resources. We consider system performance under a many-user asymptotic. We distinguish two scenarios, namely "Distributed Server Networks" (DSN) for which requests are exogenous to the system, and "Pure P2P Networks" (PP2PN) for which requests emanate from the peers themselves. For both scenarios, we consider a loss network model of performance, and determine asymptotically optimal content placement strategies in the case of a limited content catalogue. We then turn to an alternative "large catalogue" scaling where the catalogue size scales with the peer population. Under this scaling, we establish that storage space per peer must necessarily grow unboundedly if bandwidth utilization is to be maximized. Relating the system performance to properties of a specific random graph model, we then identify a content placement strategy and a request acceptance policy which jointly maximize bandwidth utilization, provided storage space per peer grows unboundedly, although arbitrarily slowly, with system size.