Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 9
2681-2687,2693

RIA-based tracing algorithm for propagation of metapopulation networks

Yang Cheng1
Wang Jianbo1,2
Xu Xiaoke3,4
Du Zhanwei2
1. School of Computer Science, Southwest Petroleum University, Chengdu 610500, China
2. School of Public Health, University of Hong Kong, Hong Kong 999077, China
3. Center for Computational Communication Research, Beijing Normal University, Zhuhai Guangdong 519085, China
4. School of Journalism & Communication, Beijing Normal University, Beijing 100875, China
DOI: 10.19734/j.issn.1001-3695.2023.02.0034

Abstract

The spread of epidemics poses a significant threat to the entire human community. Therefore, it is critical to identify the sources of transmission quickly and take timely control measures. However, the diversity of epidemic transmission processes and information uncertainty makes it challenging to identify the sources of transmission quickly and accurately. This paper proposed a new algorithm for identifying transmission sources in a metapopulation network by combining the reverse infection algorithm and Markov chain theory. The algorithm firstly used a Markov chain to initially estimate the time when a subpopulation was infected, and the infected subpopulation obtained its own identity information based on the infection time. Then, it traversed all subpopulations that obtained the identity information of the infected subpopulation and spreaded the collected identity information of the infected subpopulation to all its neighbors. Finally, the spreading source of the metapopulation network could be inferred based on the temporal order in which all the identity information of the infected subpopulation was obtained. Simulation experiments conducted on real airports networks and artificial networks show that the accuracy of this algorithm is significantly improved compared to other algorithms, regardless of whether all or partial of the infection snapshots are known. This algorithm is well-suited for metapopulation networks such as aviation networks and is also useful for real-world epidemic transmission tracing and control.

Foundation Support

国家自然科学基金面上项目(62173065)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.02.0034
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 9
Section: Algorithm Research & Explore
Pages: 2681-2687,2693
Serial Number: 1001-3695(2023)09-019-2681-07

Publish History

[2023-04-19] Accepted Paper
[2023-09-05] Printed Article

Cite This Article

阳成, 王建波, 许小可, 等. 基于反向感染的复合种群网络传播溯源算法 [J]. 计算机应用研究, 2023, 40 (9): 2681-2687,2693. (Yang Cheng, Wang Jianbo, Xu Xiaoke, et al. RIA-based tracing algorithm for propagation of metapopulation networks [J]. Application Research of Computers, 2023, 40 (9): 2681-2687,2693. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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