The Epidemic Spreading Mechanism and Dynamic Characteristics on Signatured Networks

doi:10.13190/j.jbupt.2020-145

Journal of Beijing University of Posts and Telecommunications ›› 2021, Vol. 44 ›› Issue (3): 73-78.doi: 10.13190/j.jbupt.2020-145

• PAPERS • Previous Articles Next Articles

The Epidemic Spreading Mechanism and Dynamic Characteristics on Signatured Networks

ZHUO Xin-jian, WANG Wen-xuan, LI Hui-jia

School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2020-09-30 Online:2021-06-28 Published:2021-06-23

Abstract

Abstract: Spreading behavior and its dynamic evolution in the context of big data are diversified, and thousands of information dissemination models have been developed. In this paper, aiming at the signatured network model with multi-types individuals, the spreading behavior and dynamical properties were explored. Firstly, the improved signatured-susceptible-infected-susceptible (S-SIS) model is applied to the signatured network, and then in order to simulate the spreading dynamical process. Specially, and simulate the dynamic evolution of the infection, the assumption in the existing model that the infection probability is constant is improved, an infection probability equation that changes in real time is constructed, and the spreading behavior in the signatured network is accurately simulated. Finally, mean filed analysis and Monte Carlo simulation is made to get the simulation result of the model. By adjusting the parameters and comparing the results, useful conclusions can be drawn. In order to observe the performance of networks with different topologies, Erdos-Rainey random network and scale-free network are simulated to observe the characteristic with different topology of networks, and the difference is observed in the simulation results.

Key words: signatured network, susceptible-infected-susceptible model, dynamic evolution process, Monte Carlo algorithm, mean filed analysis

CLC Number:

TN911.22

ZHUO Xin-jian, WANG Wen-xuan, LI Hui-jia. The Epidemic Spreading Mechanism and Dynamic Characteristics on Signatured Networks[J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(3): 73-78.

References

[1] 郭世泽,陆哲明.复杂网络基础理论[M].北京:科学出版社,2012:120-135.
[2] Preciado V M, Zargham M, Enyioha C, et al. Optimal resource allocation for network protection against spread-ing processes[J]. IEEE Transactions on Control of Network Systems, 2014, 1(1):99-108.
[3] Pastor-Satorras R, Castellano C, Van Mieghem P, et al. Epidemic processes in complex networks[J]. Reviews of Modern Physics, 2015, 87(3):925-979.
[4] Kimura M, Saito K, Motoda H. Efficient estimation of influence functions for SIS model on social networks[C]//IJCAI-09 Conference. Pasadena:IJCAI Press, 2009:2046-2051.
[5] Paarporn K, Eksin C, Weitz J S, et al. Networked SIS epidemics with awareness[J]. IEEE Transactions on Computational Social Systems, 2017, 4(3):93-103.
[6] Xiao Yunpeng, Song Chenguang, Liu Yanbing. Social hotspot propagation dynamics model based on multidimensional attributes and evolutionary games[J]. Communications in Nonlinear Science and Numerical Simulation,2019,67:13-25.
[7] Ye Jihang, Cheng Hong, Zhu Zhe, et al. Predicting posi-tive and negative links in signed social networks by transfer learning[C]//22nd International Conference on World Wide Web. New York:Association for Computing Machinery Press, 2013:1477-1488.
[8] Jacob C, Viet A F. Epidemiological modeling in a branching population:particular case of a general SIS model with two age classes[J]. Mathematical Biosciences, 2003, 182(1):93-111.
[9] Kessler D A. Epidemic size in the SIS model of endemic infections[J]. Journal of Applied Probability, 2008, 45(3):757-778.
[10] Shi Hongjing, Duan Zhisheng, Chen Guanrong. An SIS model with infective medium on complex networks[J]. Physica A:Statistical Mechanics and Its Applications, 2008, 387(8-9):2133-2144.
[11] Leskovec J, Huttenlocher D, Kleinberg J. Signed networks in social media[C]//SIGCHI Conference on Human Factors in Computing Systems. New York:Association for Computing Machinery Press, 2010:1361-1370.
[12] Tang J, Chang Y, Aggarwal C, et al. A survey of signed network mining in social media[J]. ACM Computing Surveys (CSUR), 2016, 49(3):1-37.
[13] Van Mieghem P. The N-intertwined SIS epidemic network model[J]. Computing, 2011, 93(2-4):147-169.
[14] Ganesh A, Massoulié L, Towsley D. The effect of network topology on the spread of epidemics[C]//IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Miami:IEEE Press, 2005:1455-1466.
[15] Van Mieghem P. Performance analysis of communications networks and systems[M]. London:Cambridge University Press, 2009:179-228.

The Epidemic Spreading Mechanism and Dynamic Characteristics on Signatured Networks

RichHTML

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	YUAN Jianguo, YU Linfeng, YOU Wei, PANG Yu. An SCL-Flip Decoding Algorithm of Polar Codes to Optimize the Error Pattern Set [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(4): 76-82.
[2]	. Scheme of Maximizing Tradeoff for the IRS-aided Downlink NOMA Systems [J]. Journal of Beijing University of Posts and Telecommunications, 0, (): 0-0.
[3]	. Fog Node Contribution Degree Based Task Offloading Algorithm for Heterogeneous Cellular Network [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(2): 37-42.
[4]	. Encoding and compression method of 3D skeleton data for semantic communication [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(6): 62-69.
[5]	Ze-Yu Wang Meng-Fei ZHANG Mugen Peng. Study on Handover Mechanism in Non-terrestrial Networks with Transparent Satellites [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(6): 105-112.
[6]	Mugen Peng. Preamble Design for Low Earth Orbit Communication Systems [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(6): 78-84.
[7]	. Polar Coded Modulation for 6G System [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(6): 1-11.
[8]	ZHANG Shunwai, XIA Zihan. Construction and Performance Analysis of SWIPT-Based Product Polar Coded Cooperation [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(5): 54-59.
[9]	Hai YingZhao Zi huiGAO. Automatic generation method of turtle back pattern based on mathematical rules [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(4): 119-125.
[10]	ZHAO Haiying, XIE Guangpeng, GAO Zihui. Automatic Generation Method of Turtle Back Pattern Based on Mathematical Rules [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(4): 110-115.
[11]	GUO Shize, Lü Renjian, HE Mingshu, ZHANG Jie, YU Saisai. Application of Flow Spectrum Theory in Network Defense [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(3): 19-25.
[12]	WANG Huiqin, YANG Lirong, PENG Qingbin, CAO Minghua, CHEN Dan. O-OFDM-DIM Based on Discrete Wavelet Transform [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(3): 57-63.
[13]	LIU Xiao-ming, QI Tao, GAN Lu. A Broadband Reflective Polarization Rotator [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(6): 20-25,32.
[14]	LIU Shao-hua, LI Ming-hao, LI Zhao-xin, MAO Tian-lu, LIU Jing. Neural Radiance Field by Joint Sampling [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(6): 109-115.
[15]	ZHAO Hai-ying, LI Huan-hong, HOU Xiao-gang. Evaluation Method of Traditional Pattern Vector Diagram Based on Perception Drive [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(6): 53-58.