Asynchronous Gossip in Smartphone Peer-to-Peer Networks

TL;DR

This paper introduces a new asynchronous gossip algorithm tailored for smartphone peer-to-peer networks, providing efficient information dissemination with theoretical guarantees and practical applicability.

Contribution

It presents the first efficient asynchronous gossip strategy for smartphone networks, along with a new synchronous algorithm and lower bounds, advancing both theory and practical implementation.

Findings

New asynchronous gossip algorithm achieves efficient information spreading.

Synchronous algorithm has faster round complexity and simpler operation.

Proven lower bounds show near-optimality of solutions.

Abstract

In this paper, we study gossip algorithms in communication models that describe the peer-to-peer networking functionality included in most standard smartphone operating systems. We begin by describing and analyzing a new synchronous gossip algorithm in this setting that features both a faster round complexity and simpler operation than the best-known existing solutions. We also prove a new lower bound on the rounds required to solve gossip that resolves a minor open question by establishing that existing synchronous solutions are within logarithmic factors of optimal. We then adapt our synchronous algorithm to produce a novel gossip strategy for an asynchronous model that directly captures the interface of a standard smartphone peer-to-peer networking library (enabling algorithms described in this model to be easily implemented on real phones). Using new analysis techniques, we prove that this asynchronous strategy efficiently solves gossip. This is the first known efficient asynchronous information dissemination result for the smartphone peer-to-peer setting. We argue that our new strategy can be used to implement effective information spreading subroutines in real world smartphone peer-to-peer network applications, and that the analytical tools we developed to analyze it can be leveraged to produce other broadly useful algorithmic strategies for this increasingly important setting.