Target observation of complex networks

TL;DR

This paper addresses the problem of observing specific parts of complex networks with limited measurements by proposing algorithms to identify minimal node sets for effective target observation.

Contribution

It introduces a target minimal dominating set problem as a generalization of classical problems and provides three algorithms for approximation.

Findings

Algorithms outperform existing methods in identifying minimal dominating sets.

Numerical results validate the effectiveness on both random and real-world networks.

Proposed methods achieve efficient target observation with fewer measurements.

Abstract

How to observe the state of a network from a limited number of measurements has become an important issue in complex networks, engineering, communication, epidemiology, etc. Under some scenarios, it is neither unfeasible nor unnecessary to observe the entire network. Therefore, we investigate the target observation of a network in this paper. We propose a target minimal dominating set problem corresponding to target observation, which is a natural generalization of classical minimal dominating set problem. Three algorithms are proposed to approximate the minimum set of occupied nodes sufficient for target observation. Extensive numerical results on computer-generated random networks and real-world networks demonstrate that the proposed algorithms offer superior performance in identification of a target minimal dominating set.