Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/179401
Title: Sufficient control of complex networks
Authors: Li, Xiang
Li, Guoqi
Gao, Leitao
Li, Beibei
Xiao, Gaoxi
Keywords: Engineering
Issue Date: 2024
Source: Li, X., Li, G., Gao, L., Li, B. & Xiao, G. (2024). Sufficient control of complex networks. Physica A: Statistical Mechanics and Its Applications, 642, 129751-. https://dx.doi.org/10.1016/j.physa.2024.129751
Project: RG19/20
Journal: Physica A: Statistical Mechanics and its Applications
Abstract: In this paper, we propose to study sufficient control of complex networks, which is to control a sufficiently large portion of the network, where only the quantity of controllable nodes matters. To the best of our knowledge, this is the first time that such a problem is investigated. We prove that the sufficient controllability problem can be converted into a minimum-cost flow problem, for which an algorithm with polynomial complexity can be devised. Further, we study the problem of minimum-cost sufficient control, which is to drive a sufficiently large subset of the network nodes to any predefined state with the minimum cost using a given number of controllers. The problem is NP-hard. We propose an “extended L0-norm-constraint-based Projected Gradient Method” (eLPGM) algorithm, which achieves suboptimal solutions for the problems at small or medium sizes. To tackle the large-scale problems, we propose to convert the control problem into a graph problem and devise an efficient low-complexity “Evenly Divided Control Paths” (EDCP) algorithm to tackle the graph problem. Simulation results on both synthetic and real-life networks are provided, demonstrating the satisfactory performance of the proposed methods.
URI: https://hdl.handle.net/10356/179401
ISSN: 0378-4371
DOI: 10.1016/j.physa.2024.129751
Schools: School of Electrical and Electronic Engineering 
Rights: © 2024 Elsevier B.V. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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