Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144369
Title: Breakup of directed multipartite networks
Authors: Cai, Qing
Pratama, Mahardhika
Alam, Sameer
Ma, Chunyao
Liu, Jiming
Keywords: Engineering::Aeronautical engineering
Issue Date: 2019
Source: Cai, Q., Pratama, M., Alam, S., Ma, C., & Liu, J. (2020). Breakup of directed multipartite networks. IEEE Transactins on Network Science and Engineering, 7(3), 947-960. doi:10.1109/TNSE.2019.2894142
Journal: IEEE Transactins on Network Science and Engineering 
Abstract: A complex network in reality often consists of profuse components, which might suffer from unpredictable perturbations. Because the components of a network could be interdependent, therefore the failures of a few components may trigger catastrophes to the entire network. It is thus pivotal to exploit the robustness of complex networks. Existing studies on network robustness mainly deal with interdependent or multilayer networks; little work is done to investigate the robustness of multipartite networks, which are an indispensable part of complex networks. Here, we plumb the robustness of directed multipartite networks. To be specific, we exploit the robustness of bi-directed and unidirectional multipartite networks in face of random node failures. We, respectively, establish cascading and non-cascading models based on the largest connected component concept for depicting the dynamical processes on bi-directed and unidirectional multipartite networks subject to perturbations. Based on our developed models, we, respectively, derive the corresponding percolation theories for mathematically computing the robustness of directed multipartite networks subject to random node failures. We unravel the first-order and second-order phase transition phenomena on the robustness of directed multipartite networks. The correctness of our developed theories has been verified through experiments on computer-generated as well as real-world multipartite networks.
URI: https://hdl.handle.net/10356/144369
ISSN: 2327-4697
DOI: 10.1109/TNSE.2019.2894142
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work is available at: https://doi.org/10.1109/TNSE.2019.2894142
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Journal Articles

Files in This Item:
File Description SizeFormat 
Cai-w1-TNSE-v1-1009.pdf2.02 MBAdobe PDFThumbnail
View/Open

PublonsTM
Citations 50

1
Updated on Mar 6, 2021

Page view(s)

56
Updated on May 5, 2021

Download(s)

5
Updated on May 5, 2021

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.