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A collective filtering based content transmission scheme in edge of vehicles

Wang, Xiaojie et al.

Information sciences. Volume 506: (2020, January); pp 161-173 -- Elsevier

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  • Title:
    A collective filtering based content transmission scheme in edge of vehicles
  • Author: Wang, Xiaojie;
    Feng, Yufan;
    Ning, Zhaolong;
    Hu, Xiping;
    Kong, Xiangjie;
    Hu, Bin;
    Guo, Yi
  • Found In: Information sciences. Volume 506: (2020, January); pp 161-173
  • Journal Title: Information sciences
  • Subjects: Sciences de l'information--Périodiques; Computer science--Periodicals; Expert systems (Computer science)--Periodicals; Information science--Periodicals; Information science; Periodicals; Edge of vehicles--Collaborative filtering--Fog computing--Markov chains; Dewey: 003.05
  • Rights: Licensed
  • Publication Details: Elsevier
  • Abstract: Abstract With the emergence of the ever-increasing vehicular applications and booming Internet services, the requirements of low-latency and high efficient transmission among vehicles become urgent to meet, and their corresponding solutions need to be well investigated. To resolve the above challenges, we propose a fog computing-based content transmission scheme with collective filtering in edge of vehicles. We first provide a system model based on fog-based rode side units by considering location-awareness, content-caching and decentralized computing. Then, a content-caching strategy in RSUs is designed to minimize the downloading latency. Specifically, we model the moving vehicles with the two-dimensional Markov chains, and calculate the probabilities of file caching in RSUs to minimize the latency in file downloading. Each vehicle can also maintain a neighbor list to record the encounters with high similarities, and update it based on the historic and real-time contacts. Finally, we carry on the experiments based on the real-world taxi trajectories in Beijing and Shanghai, China. Simulation results demonstrate the effectiveness of our proposed method.
  • Identifier: System Number: ETOCvdc_100087617609.0x000001; Journal ISSN: 0020-0255; 10.1016/j.ins.2019.07.083
  • Publication Date: 2020
  • Physical Description: Electronic
  • Shelfmark(s): 4494.250000
  • UIN: ETOCvdc_100087617609.0x000001

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