Local Search in Unstructured Networks

TL;DR

This paper reviews message-passing algorithms for searching unstructured power-law networks, highlighting their efficiency, decentralization, and potential to reduce search traffic in peer-to-peer systems.

Contribution

It introduces and evaluates decentralized search algorithms that leverage power-law network properties, improving search efficiency and traffic reduction.

Findings

Algorithms perform well on real Gnutella networks

Search scales sub-linearly with network size

Potential to reduce network search traffic

Abstract

We review a number of message-passing algorithms that can be used to search through power-law networks. Most of these algorithms are meant to be improvements for peer-to-peer file sharing systems, and some may also shed some light on how unstructured social networks with certain topologies might function relatively efficiently with local information. Like the networks that they are designed for, these algorithms are completely decentralized, and they exploit the power-law link distribution in the node degree. We demonstrate that some of these search algorithms can work well on real Gnutella networks, scale sub-linearly with the number of nodes, and may help reduce the network search traffic that tends to cripple such networks.