Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6): 282-287.doi: 10.11896/jsjkx.200700040

• Computer Network • Previous Articles     Next Articles

Non-linear Load Capacity Model of Complex Networks

WANG Xue-guang1, ZHANG Ai-xin2, DOU Bing-lin2   

  1. 1 Department of Information Science and Technology,East China University of Political Science and Law,Shanghai 200052,China
    2 School of Cyber Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China
  • Received:2020-07-08 Revised:2020-08-19 Online:2021-06-15 Published:2021-06-03
  • About author:WANG Xue-guang,born in 1975,Ph.D,professor,is a member of China Computer Federation.His main research interests include computer networks,big data application and electronic data.
  • Supported by:
    National Key R&D Program of China (2017YFB0802103).

PDF (PC)

1172

Abstract: The study of network formation mechanism,geometric property,evolution rules,network structure analysis,behavior prediction and control gives rise to the discipline of complex network,and cascade failure process of complex network has always been concerned.This paper presents a non-linear load capacity model with two variable parameters,which is more suitable for real network,to solve the cascading failures problem of complex networks.Simulations on four different networks verify the effectiveness of the proposed model.The results show that the model can better defend against cascading failures,and has a lower investment cost and a better performance in the case of higher robustness.

Key words: Cascading failures, Complex networks, Degree correlation, Non-linear model, Robustness

CLC Number: 

  • TP393
[1]WATTS D J,STROGATZ S H.Collective dynamics of ‘small-world’ networks[J].Nature,1998,393(6684):440-442.
[2]BARABÁSI A L,ALBERT R.Emergence of scaling in random networks [J].Science,1999,286(5439):509-512.
[3]CHEN C.Connectivity in Complex Networks:Measures,Infe-rence and Optimization[C]//The Eleventh ACM International Conference on Web Search and Data Mining.2018:747-748.
[4]KATCHAGUY A,SUCHETA S.Measuring the sampling ro-bustness of complex networks[C]//The 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.2019:294-301.
[5]TANMOY C,NOSEONG P,AYUSH A,et al.Ensemble Detection and Analysis of Communities in Complex Networks[J].ACM/IMS Transactions on Data Science,2020,1(1):1-34.
[6]ARTUR K,KAMIL B,PIOTR B,et al.Influencing information spreading processes in complex networks with probability spraying[C]//The 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.2018:1038-1046.
[7]ISAAC K,AFROZA S,FRANCESCO S.Locally Optimal Control of Complex Networks [J].Physical Review Letters,2017,119(26):268301.
[8]TYLOO M,COLETTA T,JACQUOD P.Robustness of Synchrony in Complex Networks and Generalized Kirchhoff Indices [J].Physical Review Letters,2018,120(8):084101.
[9]TONG T,JIANG Y,ZHOU Y,et al.Mitigation Strategy for the Cascading Failure of Complex Networks Based on Node Capacity Control Function [J].IEEE Access,2019,7:184743-184758.
[10]KOLLI N,NARAYANASWAMY B.Influence MaximizationFrom Cascade Information Traces in Complex Networks in the Absence of Network Structure [J].IEEE Transactions on Computational Social Systems,2019,6(6):1147-1155.
[11]VEGA C J,SANCHEZ E N,CHEN G.Trajectory Tracking on Complex Networks With Non-Identical Chaotic Nodes via Inverse Optimal Pinning Control [J].IEEE Control Systems Letters,2018,2(4):635-640.
[12]SHANG Y.Subgraph Robustness of Complex Networks Under Attacks [J].IEEE Transactions on Systems,Man,and Cybernetics:Systems,2019,49(4):821-832.
[13]DADLANI A,KUMAR M S,MURUGAN S,et al.System Dynamics of a Refined Epidemic Model for Infection Propagation Over Complex Networks [J].IEEE Systems Journal,2016,10(4):1316-1325.
[14]CHEN G,LOU Y,WANG L.A Comparative Study on Control-lability Robustness of Complex Networks [J].IEEE Transactions on Circuits and Systems II:Express Briefs,2019,66(5):828-832.
[15]KLICKSTEIN I,SORRENTINO F.Control Distance and Energy Scaling of Complex Networks [J].IEEE Transactions on Network Science and Engineering,2020,7(2):726-736.
[16]PIZZUTI C,SOCIEVOLE A.A Genetic Algorithm for Impro-ving Robustness of Complex Networks[C]//2018 IEEE 30th International Conference on Tools with Artificial Intelligence(ICTAI).2018:514-521.
[17]YAMASHITA K,NAKAMURA R,OHSAKI H.A Study on Robustness of Complex Networks Against Random Node Removals[C]//2018 IEEE 42nd Annual Computer Software and Applications Conference(COMPSAC).2018:966-969.
[18]BOCCALETTI S,LATORA V,MORENO Y,et al.Complex networks:Structure and dynamics [J].Physics Reports,2006,424(4):175-308.
[19]MOTTER A E,LAI Y C.Cascade-based attacks on complex networks [J].Physical Review E,2002,66(6):065102(4).
[20]XIANG L Y,CHEN Z Q,LIU Z X,et al.A review of modeling,Analysis and Control of Complex Dynamic Networks [J].Progress in natural science,2006,16(12):1543-1551.
[21]GOH K I,KAHNG B,KIM D.Universal behavior of load distribution in scale-free networks [J].Physical Review Letters,2001,87(27):278701(4).
[22]ERDÖS P,RÉNYI A.On the evolution of random graphs [J].Publications of the Mathematical Institute of the Hungarian Academy of Sciences,1960,5:17-60.
[23]CAID A.The AS Relationships Dataset [EB/OL].(2020-07-05).http://www.caida.org/data/active/as-relationships/.
[24]NEWMAN M E J.Assortative mixing in networks [J].Physical Review Letters,2002,89(20):208701(4).
[25]NEWMAN M E J.Mixing patterns in networks [J].Physical Review E,2003,67(2):26126(13).
[26]NOH J D.Percolation transition in networks with degree-degree correlation [J].Physical Review E,2007,76(2):26116(7).
[27]PAYNE J L,DODDS P S,EPPSTEIN M J.Information cascades on degree-correlated random networks [J].Physical Review E,2009,80(2):26125(7).
[28]SUN J T,WANG S J,HUANG Z G,et al.Effect of degree correlations on networked traffic dynamics [J].Physica A,2009,388(15):3244-3248.
[1] ZHOU Hui, SHI Hao-chen, TU Yao-feng, HUANG Sheng-jun. Robust Deep Neural Network Learning Based on Active Sampling [J]. Computer Science, 2022, 49(7): 164-169.
[2] YAN Meng, LIN Ying, NIE Zhi-shen, CAO Yi-fan, PI Huan, ZHANG Lan. Training Method to Improve Robustness of Federated Learning [J]. Computer Science, 2022, 49(6A): 496-501.
[3] ZHANG Cheng-rui, CHEN Jun-jie, GUO Hao. Comparative Analysis of Robustness of Resting Human Brain Functional Hypernetwork Model [J]. Computer Science, 2022, 49(2): 241-247.
[4] LI Jia-wen, GUO Bing-hui, YANG Xiao-bo, ZHENG Zhi-ming. Disease Genes Recognition Based on Information Propagation [J]. Computer Science, 2022, 49(1): 264-270.
[5] MU Jun-fang, ZHENG Wen-ping, WANG Jie, LIANG Ji-ye. Robustness Analysis of Complex Network Based on Rewiring Mechanism [J]. Computer Science, 2021, 48(7): 130-136.
[6] MA Yuan-yuan, HAN Hua, QU Qian-qian. Importance Evaluation Algorithm Based on Node Intimate Degree [J]. Computer Science, 2021, 48(5): 140-146.
[7] YIN Zi-qiao, GUO Bing-hui, MA Shuang-ge, MI Zhi-long, SUN Yi-fan, ZHENG Zhi-ming. Autonomous Structural Adjustment of Crowd Intelligence Network: Begin from Structure of Biological Regulatory Network [J]. Computer Science, 2021, 48(5): 184-189.
[8] ZHAO Man-yu, YE Jun. Synchronization of Uncertain Complex Networks with Sampled-data and Input Saturation [J]. Computer Science, 2021, 48(11A): 481-484.
[9] TONG Xin, WANG Bin-jun, WANG Run-zheng, PAN Xiao-qin. Survey on Adversarial Sample of Deep Learning Towards Natural Language Processing [J]. Computer Science, 2021, 48(1): 258-267.
[10] WU Qing-hong, GAO Xiao-dong. Face Recognition in Non-ideal Environment Based on Sparse Representation and Support Vector Machine [J]. Computer Science, 2020, 47(6): 121-125.
[11] LU Dong-dong, WU Jie, LIU Peng, SHENG Yong-xiang. Analysis of Key Developer Type and Robustness of Collaboration Network in Open Source Software [J]. Computer Science, 2020, 47(12): 100-105.
[12] CHEN Xiao-wen, LIU Guang-shuai, LIU Wang-hua, LI Xu-rui. Blurred Image Recognition Based on LoG Edge Detection and Enhanced Local Phase Quantization [J]. Computer Science, 2020, 47(12): 197-204.
[13] ZHAO Sai, LIU Hao, WANG Yu-feng, SU Hang, YAN Ji-wei. Fuzz Testing of Android Inter-component Communication [J]. Computer Science, 2020, 47(11A): 303-309.
[14] GAO Li-jian,MAO Qi-rong. Environment-assisted Multi-task Learning for Polyphonic Acoustic Event Detection [J]. Computer Science, 2020, 47(1): 159-164.
[15] ZHAO Lei, ZHOU Jin-he. ICN Energy Efficiency Optimization Strategy Based on Content Field of Complex Networks [J]. Computer Science, 2019, 46(9): 137-142.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.