Impact of community structure on information transfer

TL;DR

This paper studies how community structures in complex networks influence information transfer efficiency, proposing algorithms that leverage community knowledge to optimize routing and capacity, with intermediate and hierarchical community levels being most effective.

Contribution

It introduces a novel analysis of community structure effects on information transfer and proposes community-aware routing algorithms that enhance network performance.

Findings

Fuzzy community structures improve packet delivery efficiency.

Community-aware routing algorithms outperform traditional methods.

Hierarchical community knowledge significantly increases network capacity.

Abstract

The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery that those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount.