Towards Optimal Robustness of Network Controllability: An Empirical Necessary Condition
Yang Lou, Lin Wang, Kim Fung Tsang, Guanrong Chen

TL;DR
This paper investigates the relationship between network topology and controllability robustness, proposing an empirical necessary condition (ENC) that guides the design of more robust networks through edge rectification, validated on synthetic and real-world data.
Contribution
It introduces an empirical necessary condition (ENC) for optimal network controllability robustness and develops an edge rectification method to achieve it.
Findings
ENC indicates optimal networks are highly homogeneous in degrees.
Edge rectification improves network controllability robustness.
Simulation confirms effectiveness of ENC and rectification on various networks.
Abstract
To better understand the correlation between network topological features and the robustness of network controllability in a general setting, this paper suggests a practical approach to searching for optimal network topologies with given numbers of nodes and edges. Since theoretical analysis seems impossible at least in the present time, exhaustive search based on optimization techniques is employed, firstly for a group of small-sized networks that are realistically workable, where \textit{exhaustive} means 1) all possible network structures with the given numbers of nodes and edges are computed and compared, and 2) all possible node-removal sequences are considered. A main contribution of this paper is the observation of an empirical necessary condition (ENC) from the results of exhaustive search, which shrinks the search space to quickly find an optimal solution. ENC shows that the…
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