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Sampling from complex networks using distributed learning automata

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  • Rezvanian, Alireza
  • Rahmati, Mohammad
  • Meybodi, Mohammad Reza

Abstract

A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

Suggested Citation

  • Rezvanian, Alireza & Rahmati, Mohammad & Meybodi, Mohammad Reza, 2014. "Sampling from complex networks using distributed learning automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 224-234.
    • Handle: RePEc:eee:phsmap:v:396:y:2014:i:c:p:224-234
    DOI: 10.1016/j.physa.2013.11.015
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    References listed on IDEAS

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    1. M. Goldstein & S. Morris & G. Yen, 2004. "Problems with fitting to the power-law distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 41(2), pages 255-258, September.
    2. Zhang, Guidong & Li, Zhong & Zhang, Bo & Halang, Wolfgang A., 2013. "Understanding the cascading failures in Indian power grids with complex networks theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3273-3280.
    3. Ibrahim Sorkhoh & Khaled A. Mahdi & Maytham Safar, 2013. "Estimation algorithm for counting periodic orbits in complex social networks," Information Systems Frontiers, Springer, vol. 15(2), pages 193-202, April.
    4. James Ma & Daniel Zeng & Huimin Zhao, 2012. "Modeling the growth of complex software function dependency networks," Information Systems Frontiers, Springer, vol. 14(2), pages 301-315, April.
    5. Tang, Jinjun & Wang, Yinhai & Liu, Fang, 2013. "Characterizing traffic time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4192-4201.
    6. Hu, Sen & Yang, Hualei & Cai, Boliang & Yang, Chunxia, 2013. "Research on spatial economic structure for different economic sectors from a perspective of a complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3682-3697.
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    Cited by:

    1. Rezvanian, Alireza & Meybodi, Mohammad Reza, 2015. "Sampling social networks using shortest paths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 254-268.
    2. Moradabadi, Behnaz & Meybodi, Mohammad Reza, 2017. "A novel time series link prediction method: Learning automata approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 422-432.
    3. Huang, Yubo & Dong, Hongli & Zhang, Weidong & Lu, Junguo, 2019. "Stability analysis of nonlinear oscillator networks based on the mechanism of cascading failures," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 5-15.
    4. Zeinab Shariat & Ali Movaghar & Mehdi Hoseinzadeh, 2017. "A learning automata and clustering-based routing protocol for named data networking," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 65(1), pages 9-29, May.
    5. Liu, Nairong & An, Haizhong & Gao, Xiangyun & Li, Huajiao & Hao, Xiaoqing, 2016. "Breaking news dissemination in the media via propagation behavior based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 44-54.
    6. Moradabadi, Behnaz & Meybodi, Mohammad Reza, 2016. "Link prediction based on temporal similarity metrics using continuous action set learning automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 361-373.

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