Information propagation modeling in a drone network using disease epidemic models

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

doi:10.1109/ICUFN.2016.7536986

Information propagation modeling in a drone network using disease epidemic models

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

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 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 language	English
Title of host publication	ICUFN 2016 - 8th International Conference on Ubiquitous and Future Networks
Publisher	IEEE Computer Society
Pages	79-81
Number of pages	3
ISBN (Electronic)	9781467399913
DOIs	https://doi.org/10.1109/ICUFN.2016.7536986
Publication status	Published - 2016 Aug 9
Event	8th International Conference on Ubiquitous and Future Networks, ICUFN 2016 - Vienna, Austria Duration: 2016 Jul 5 → 2016 Jul 8

Publication series

Name	International Conference on Ubiquitous and Future Networks, ICUFN
Volume	2016-August
ISSN (Print)	2165-8528
ISSN (Electronic)	2165-8536

Other

Other	8th International Conference on Ubiquitous and Future Networks, ICUFN 2016
Country	Austria
City	Vienna
Period	16/7/5 → 16/7/8

Keywords

drone
network
real time
transmission

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Hardware and Architecture

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

Access to Document

10.1109/ICUFN.2016.7536986

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Kim, Y., Kim, J. K., Seok, J., & Kim, B. D. (2016). Information propagation modeling in a drone network using disease epidemic models. In ICUFN 2016 - 8th International Conference on Ubiquitous and Future Networks (pp. 79-81). [7536986] (International Conference on Ubiquitous and Future Networks, ICUFN; Vol. 2016-August). IEEE Computer Society. https://doi.org/10.1109/ICUFN.2016.7536986

Information propagation modeling in a drone network using disease epidemic models. / Kim, Yoojoong; Kim, Jong Kook ; Seok, Junhee; Kim, Byoung Du.

ICUFN 2016 - 8th International Conference on Ubiquitous and Future Networks. IEEE Computer Society, 2016. p. 79-81 7536986 (International Conference on Ubiquitous and Future Networks, ICUFN; Vol. 2016-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kim, Y, Kim, JK , Seok, J & Kim, BD 2016, Information propagation modeling in a drone network using disease epidemic models. in ICUFN 2016 - 8th International Conference on Ubiquitous and Future Networks., 7536986, International Conference on Ubiquitous and Future Networks, ICUFN, vol. 2016-August, IEEE Computer Society, pp. 79-81, 8th International Conference on Ubiquitous and Future Networks, ICUFN 2016, Vienna, Austria, 16/7/5. https://doi.org/10.1109/ICUFN.2016.7536986

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title = "Information propagation modeling in a drone network using disease epidemic models",

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.",

keywords = "drone, network, real time, transmission",

author = "Yoojoong Kim and Kim, {Jong Kook} and Junhee Seok and Kim, {Byoung Du}",

note = "Funding Information: This work was supported by grants from the National Research Foundation of Korea (NRF-2014R1A1A2A16050527, NRF-2015R1A2A1A16074932).; 8th International Conference on Ubiquitous and Future Networks, ICUFN 2016 ; Conference date: 05-07-2016 Through 08-07-2016",

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AB - 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.

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Information propagation modeling in a drone network using disease epidemic models

Abstract

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Keywords

ASJC Scopus subject areas

UN SDGs

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