On Democracy in Peer-to-Peer systems

TL;DR

This paper proposes a gossip-based method for peer-to-peer networks to collectively identify community leaders, enabling broader community detection beyond individual node similarities for improved information diffusion.

Contribution

It introduces a gossip-like algorithm for decentralized community leader election, enhancing the discovery of broader peer communities in P2P networks.

Findings

Leads to more effective community detection in P2P networks.

Enables peers to identify and join broader interest communities.

Improves information diffusion across the network.

Abstract

The information flow inside a P2P network is highly dependent on the network structure. In order to ease the diffusion of relevant data toward interested peers, many P2P protocols gather similar nodes by putting them in direct contact. With this approach the similarity between nodes is computed in a point-to-point fashion: each peer individually identifies the nodes that share similar interests with it. This leads to the creation of a sort of "private" communities, limited to each peer neighbors list. This "private" knowledge do not allow to identify the features needed to discover and characterize the correlations that collect similar peers in broader groups. In order to let these correlations to emerge, the collective knowledge of peers must be exploited. One common problem to overcome in order to avoid the "private" vision of the network, is related to how distributively determine the representation of a community and how nodes may decide to belong to it. We propose to use a gossip-like approach in order to let peers elect and identify leaders of interest communities. Once leaders are elected, their profiles are used as community representatives. Peers decide to adhere to a community or another by choosing the most similar representative they know about.