Spread of Influence and Content in Mobile Opportunistic Networks

TL;DR

This paper models how content spreads in mobile networks through influence and epidemic copying, deriving optimal policies and analyzing parameter effects in a decentralized setting.

Contribution

It introduces a joint influence and epidemic content spread model in mobile networks and proves the optimality of a time-threshold copying policy.

Findings

Time-threshold policy is optimal for copying to relays.

Derived fluid limits for joint evolution models.

Simulations show effects of system parameters.

Abstract

We consider a setting in which a single item of content (such as a song or a video clip) is disseminated in a population of mobile nodes by opportunistic copying when pairs of nodes come in radio contact. We propose and study models that capture the joint evolution of the population of nodes interested in the content (referred to as destinations), and the population of nodes that possess the content. The evolution of interest in the content is captured using an influence spread model and the content spread occurs via epidemic copying. Nodes not yet interested in the content are called relays; the influence spread process converts relays into destinations. We consider the decentralized setting, where interest in the content and the spread of the content evolve by pairwise interactions between the mobiles. We derive fluid limits for the joint evolution models and obtain optimal policies for copying to relay nodes in order to deliver content to a desired fraction of destinations. We prove that a time-threshold policy is optimal while copying to relays. We then provide insights into the effects of various system parameters on the co-evolution model through simulations.