Optimal search strategies on complex networks

TL;DR

This paper investigates how agents can efficiently search for targets on complex networks by combining local and long-range hops, revealing an optimal strategy tailored to network topology.

Contribution

It introduces a model of search dynamics on complex networks with combined local and long-range moves, identifying the optimal balance for maximum search efficiency.

Findings

Existence of an optimal combination of local and long-range hops.

Optimal strategy depends on network topology.

Enhanced search efficiency compared to single-hop strategies.

Abstract

Complex networks are ubiquitous in nature and play a role of paramount importance in many contexts. Internet and the cyberworld, which permeate our everyday life, are self-organized hierarchical graphs. Urban traffic flows on intricate road networks, which impact both transportation design and epidemic control. In the brain, neurons are cabled through heterogeneous connections, which support the propagation of electric signals. In all these cases, the true challenge is to unveil the mechanisms through which specific dynamical features are modulated by the underlying topology of the network. Here, we consider agents randomly hopping along the links of a graph, with the additional possibility of performing long-range hops to randomly chosen disconnected nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network.