Simplification of networks via conservation of path diversity and minimisation of the search information

TL;DR

This paper introduces a network simplification method that preserves alternative paths by aggregating nodes into super-nodes, enabling efficient path description and analysis of large networks.

Contribution

It proposes a novel network aggregation technique that maintains path diversity and minimizes information needed to describe network navigation, improving scalability.

Findings

Scaling behavior observed between total path information and skeleton network information

Method reduces computational cost for large network path analysis

Application to real networks demonstrates effectiveness

Abstract

Alternative paths in a network play an important role in its functionality as they can maintain the information flow under node/link failures. In this paper we explore the navigation of a network taking into account the alternative paths and in particular how can we describe this navigation in a concise way. Our approach is to simplify the network by aggregating into groups the nodes that do not contribute to alternative paths. We refer to these groups as super-nodes, and describe the post-aggregation network with super-nodes as the skeleton network. We present a method to describe with the least amount of information the paths in the super--nodes and skeleton network. Applying our method to several real networks we observed that there is scaling behaviour between the information required to describe all the paths in a network and the minimal information to describe the paths of its skeleton. We show how from this scaling we can evaluate the information of the paths for large networks with less computational cost.