Controllability analysis of directed networks in finite states based on pruning motif isomorph

TL;DR

This paper introduces a pruning and motif isomorph search method for identifying driver nodes in directed networks with finite states, effectively handling large networks while considering node costs.

Contribution

It proposes a novel control method that combines pruning, motif matching, and path search to efficiently find driver nodes with low time complexity.

Findings

Method guarantees accurate driver node identification.

Algorithm efficiently handles large networks.

Control achieved with no more than 16.84% driver nodes.

Abstract

The current driver nodes search methods are difficult to cope with large networks, and the solution process does not consider the node cost. In order to solve the practical control problem of networks with different node costs in finite states, this paper proposes a pruning and motif isomorph search method for driver node set. Firstly, we prove the sufficient conditions for the network to be strictly controllable under partial nodes control, then we classify the nodes and prove the equivalence controllability of the pruning network, and then we establish three models of maximum augmenting path search, local pruning and motif matching to form a complete driver nodes set search algorithm. Finally, the algorithm is validated by real networks. The results show that our method not only guarantee the accuracy of search results, but also has the low time complexity, which can efficiently handle large networks, and no more than 16.84% of the maximum driver nodes can control the whole network.