Research on Active Push Method of Multi-source Patrol Information in Large-Capacity Communication Network

  • Yan-song HuEmail author
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 301)


The traditional large-capacity communication network multi-source patrol information active push method has the defect of poor push effect. For this reason, the active push method of multi-source patrol information in large-capacity communication network is proposed. The differential filtering method is used to preprocess the collected multi-source patrol information, based on the processed multi-source patrol information obtained above. The multi-source patrol information is grouped and clustered to obtain a multi-source patrol information feature set, and the obtained multi-source patrol information feature set is collaboratively filtered to obtain a user-neighbor neighbor multi-source patrol information set. The active push algorithm is used to actively push the nearest neighbor multi-source patrol information, which realizes the active push of multi-source patrol information in the large-capacity communication network. Through experiments, the proposed multi-source patrol information active push method push response time of the large-capacity communication network is 4.1 S less than the traditional method. The proposed multi-source patrol information active push method for large-capacity communication network has better push effect.


High capacity Communications network Multiple sources Inspection information Push 


  1. 1.
    Zhu, X., Yu, Z., Lin, Y., et al.: Research on multi-source geographic data push method based on model requirement template matching. Geogr. Geogr. Inf. Sci. 32(1), 24–28 (2016)Google Scholar
  2. 2.
    Lu, J., Wang, C., Xiao, G., et al.: Research and application of cloud push platform for multi-source heterogeneous data. Comput. Sci. 43(s1), 12–15 (2016)Google Scholar
  3. 3.
    Liu, J.: Huadian University Tong Qinjiashan 100,000 kW photovoltaic power station UAV automatic inspection and hot spot image automatic recognition. Solar Energy 56(5), 45–48 (2017)Google Scholar
  4. 4.
    Liu, J.: Practice and understanding of the construction of integrated information system for oil field exploration and development. Contemp. Petrochem. 24(10), 46–50 (2016)Google Scholar
  5. 5.
    Li, W., Wang, Y., Xu, B., et al.: The research on network management and online monitoring for communication network for smart distribution and consumption network. Autom. Instrum. 4, 27–30 (2018)Google Scholar
  6. 6.
    Ding, W., Qiu, W., Chen, D., et al.: Application research of PTN technology in Shaoxing power telecommunication network. Zhejiang Electric Power 37(5), 22–26 (2018)Google Scholar
  7. 7.
    Xie, Y., Wu, L., Zhang, S., et al.: Realization of security protection system for power communication network based on bigdata. Electron. Des. Eng. 25(19), 131–135 (2017)Google Scholar
  8. 8.
    Cui, L., Geng, Z., Shu, Q., et al.: Key link identification in electric power communication network considering grid correlation degree. Electric Power Constr. 38(5), 124–132 (2017)Google Scholar
  9. 9.
    Liu, Y.: Design and implementation of computer room patrol management system based on NFC technology. Financ. Technol. Time 10, 48–51 (2017)Google Scholar
  10. 10.
    Liu, X.: Application of network communication technology in reality. Digit. Commun. World 169(01), 206 (2019)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.Liaoning Petrochemical Vocational and TechnologyJinzhouChina

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