Assessing edge-coupled interdependent network disintegration via rank aggregation and elite enumeration

doi:10.1088/1674-1056/ace682

Abstract The disintegration of networks is a widely researched topic with significant applications in fields such as counter-terrorism and infectious disease control. While the traditional approaches for achieving network disintegration involve identifying critical sets of nodes or edges, limited research has been carried out on edge-based disintegration strategies. We propose a novel algorithm, i.e., a rank aggregation elite enumeration algorithm based on edge-coupled networks (RAEEC), which aims to implement tiling for edge-coupled networks by finding important sets of edges in the network while balancing effectiveness and efficiency. Our algorithm is based on a two-layer edge-coupled network model with one-to-one links, and utilizes three advanced edge importance metrics to rank the edges separately. A comprehensive ranking of edges is obtained using a rank aggregation approach proposed in this study. The top few edges from the ranking set obtained by RAEEC are then used to generate an enumeration set, which is continuously iteratively updated to identify the set of elite attack edges. We conduct extensive experiments on synthetic networks to evaluate the performance of our proposed method, and the results indicate that RAEEC achieves a satisfactory balance between efficiency and effectiveness. Our approach represents a significant contribution to the field of network disintegration, particularly for edge-based strategies.

Keywords: edged-coupled rank aggregation interdependent networks elite enumeration

Received: 04 April 2023
Revised: 03 July 2023
Accepted manuscript online: 12 July 2023

PACS:

89.75.Fb

(Structures and organization in complex systems)

Fund: This work was supported by the National Natural Science Foundation of China (Grant Nos. 61877046, 12271419, and 62106186), the Natural Science Basic Research Program of Shaanxi (Program No. 2022JQ-620), and the Fundamental Research Funds for the Central Universities (Grant Nos. XJS220709, JB210701, and QTZX23002).

Corresponding Authors: Yi-Guang Bai
E-mail: ygbai@foxmail.com

Cite this article:

Yong-Hui Li(李咏徽), San-Yang Liu(刘三阳), and Yi-Guang Bai(白艺光) Assessing edge-coupled interdependent network disintegration via rank aggregation and elite enumeration 2023 Chin. Phys. B 32 118901

[1] Rubinov M and Sporns O 2010 NeuroImage 1059 52
[2] A Barrat, S Boccaletti, G Caldarelli, A Chessa, V Latora and A E Motter 2014 J. Phys. A:Math. Theor. 41 220301
[3] Ding L H, Sun B and Shi P 2019 Acta Phys. Sin. 68 128902 (in Chinese)
[4] Lv L T, Wu J L and Lv H 2020 J. Phys.:Conf. Ser. 1533 032076
[5] Jin Y L, Guo R Z, Yu X Q and Shen L Q 2021 Chin. Phys. B 30 120505
[6] Zhong S, Zhang H and Deng Y 2022 Inf. Sci. 610 944
[7] Ruan Y R, Lao S Y, Xiao Y D, Wang J D and Bai L 2016 Chin. Phys. Lett 33 028910
[8] Yu H, Cao X, Liu Z and Li Y J 2017 Physica A318 486
[9] Huang L Y, Tang P C, Huo Y L, Zheng Y and Cheng X F 2019 Acta Phys. Sin. 68 128901 (in Chinese)
[10] Ullah A, Wang B, Sheng J F and Khan N 2022 Appl. Intell.16586 52
[11] Yu E Y, Fu Y, Chen X, Xie M and Chen D B 2020 Sci. Rep. 10 12494
[12] Yu H, Cao X, Liu Z and Li Y J 2017 Physica A 486 318
[13] Neal Z 2013 Social Network Analysis and Mining 915 3
[14] Scutari M and Nagarajan R 2011 Artif. Intell. Med. 207 57
[15] Lu J C, Bao D L, Qian K, Zhang S, Chen H, Lin X, Du S H and Gao H J 2017 ACS Nano 1689 2
[16] González A D, Dueeñas-Osorio L, Sánchez-Silva M and Medaglia A L 2016 Comput.-Aided Civ. Infrastruct. Eng. 334 31
[17] Han W T, Yi P, Ma H L, Zhang P and Tian L 2016 Acta Phys. Sin. 68 186401 (in Chinese)
[18] Xu X, Zhu C, Wang Q Y, Zhu X Q and Zhou Y 2020 Sci. Rep. 2691 10
[19] Wang J E, Liu S Y, Aljmiai A and Bai Y G 2021 Chin. Phys. B 8 30
[20] Sridhar S, Hahn A and Govindarasu M 2012 Proc. IEEE 210 100
[21] Girvan M and Newman M E J 2001 Proc. Natl. Acad. Sci. USA 99 7281
[22] Yu E Y, Chen D B and Zhao J Y 2018 Sci. Rep. 14469 8
[23] Holme P, Kim B J, Yoon C and Han S K 2002 Phys. Rev. E 056109 65
[24] Chen D B, Lv L Y, Shang M S, Zhang Y C and Zhou T 2012 Physica A 1777 391
[25] Cheng X Q, Ren F X, Shen H W, Zhang Z K and Zhou T 2010 J. Stat. Mech.:Theory Exp. 10011 2010
[26] Liu Y, Tang M, Zhou T and Do Y 2015 Sci. Rep. 5 13172
[27] Zhao N, Li J, Wang J, Li T, Yu Y and Zhou T 2020 Physica A 123877 548
[28] Onnela J P, Saramäki J, Hyvönen J, et al. 2006 Proc. Natl. Acad. Sci. USA 7332 104
[29] Restrepo J G, Ott E and R B 2006 Phys. Rev. Lett. 094102 97 9
[30] Bo O Y, Xia Y X, Wang C, Ye Q Yan Z and Tang Q 2018 IEEE Trans. Circuits II 1244 65
[31] Zhang Q F and Li H 2007 IEEE Trans. Evol. Comput. 712 11
[32] Datta T, Srinidhi N, Chockalingam A and Rajan B S 2010 IEEE Commun. Lett. 1107 14
[33] Xiao Y, Deng H Z, Lu X and Wu J 2019 J. Oper. Res. Soc. 227 72
[34] Barabasi A L 2009 Science 412 325
[35] Erdös P and Rényi A 2006 Science 257 286
[36] Weeden K A and Cornwell B 2020 Sociol. Sci. 222 7

[1]	Percolation transitions in edge-coupled interdependent networks with directed dependency links Yan-Li Gao(高彦丽), Hai-Bo Yu(于海波), Jie Zhou(周杰), Yin-Zuo Zhou(周银座), and Shi-Ming Chen(陈世明). Chin. Phys. B, 2023, 32(9): 098902.

No Suggested Reading articles found!

Viewed

Full text

Abstract

Cited

Metrics
Related Articles

Assessing edge-coupled interdependent network disintegration via rank aggregation and elite enumeration

Cite this article:

Online attention