Information propagation modeling in a drone network using disease epidemic models

Yoojoong Kim, Jong Kook Kim, Junhee Seok, Byoung Du Kim

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

4 Citations (Scopus)

Abstract

Drones transmit and receive packets with each other in a wireless network setting. Packet transmission among drones fails for various reasons. The pattern of information propagation through the packet transmission in a drone network can be considered similar to the pattern of infectious disease transmission in a human interaction network. In this work, we use a Microscopic Markov Chain Approach (MMCA), which has been applied to model the patterns of disease epidemics in a human network, to investigate the packet transmission pattern in a microscopic scale. Throughout the simulation studies, we investigated the usefulness of MMCAs for a drone network.

Original languageEnglish
Title of host publicationICUFN 2016 - 8th International Conference on Ubiquitous and Future Networks
PublisherIEEE Computer Society
Pages79-81
Number of pages3
ISBN (Electronic)9781467399913
DOIs
Publication statusPublished - 2016 Aug 9
Event8th International Conference on Ubiquitous and Future Networks, ICUFN 2016 - Vienna, Austria
Duration: 2016 Jul 52016 Jul 8

Publication series

NameInternational Conference on Ubiquitous and Future Networks, ICUFN
Volume2016-August
ISSN (Print)2165-8528
ISSN (Electronic)2165-8536

Other

Other8th International Conference on Ubiquitous and Future Networks, ICUFN 2016
Country/TerritoryAustria
CityVienna
Period16/7/516/7/8

Bibliographical note

Funding Information:
This work was supported by grants from the National Research Foundation of Korea (NRF-2014R1A1A2A16050527, NRF-2015R1A2A1A16074932).

Publisher Copyright:
© 2016 IEEE.

Keywords

  • drone
  • network
  • real time
  • transmission

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture

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