Prediction of information propagation in a drone network by using machine learning

Jinsoo Park, Yoojoong Kim, Junhee Seok

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Drones cooperate with each other by transmitting and receiving packets. Therefore, it is important to conjecture the packet transmission rates within the network. However, the conventional methods are not suitable to describe the transmission patterns with satisfactory computing speed and accuracy. In this paper, we demonstrated that machine learning can successfully predict the transmission patterns in drone network. The packet transmission rates of a communication network with twenty drones were simulated, of which results were used to train the linear regression and Support Vector Machine with Quadratic Kernel (SVM-QK). We found out SVM-QK can precisely predict the communication between drones.

Original languageEnglish
Title of host publication2016 International Conference on Information and Communication Technology Convergence, ICTC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages147-149
Number of pages3
ISBN (Electronic)9781509013258
DOIs
Publication statusPublished - 2016 Nov 30
Event2016 International Conference on Information and Communication Technology Convergence, ICTC 2016 - Jeju Island, Korea, Republic of
Duration: 2016 Oct 192016 Oct 21

Other

Other2016 International Conference on Information and Communication Technology Convergence, ICTC 2016
CountryKorea, Republic of
CityJeju Island
Period16/10/1916/10/21

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Keywords

  • Communication
  • Drone
  • linear regression
  • Monte-Carlo method
  • Network
  • Supported Vector Machine

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing

Cite this

Park, J., Kim, Y., & Seok, J. (2016). Prediction of information propagation in a drone network by using machine learning. In 2016 International Conference on Information and Communication Technology Convergence, ICTC 2016 (pp. 147-149). [7763456] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICTC.2016.7763456