TY - GEN
T1 - Progressive ad-hoc route reconstruction using distributed UAV relays after a large-scale failure
AU - Shin, Christina Suyong
AU - Park, So Yeon
AU - Yoon, Jinyi
AU - Lee, Hyungjune
N1 - Funding Information:
This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2015R1D1A1A01057902).
Publisher Copyright:
© 2018 IEEE.
PY - 2018/6/8
Y1 - 2018/6/8
N2 - In this paper, we address a route reconstruction problem using Unmanned Aerial Vehicles (UAVs) after a large-scale disaster where stationary ad-hoc networks are severely destructed. The main goal of this paper is to improve routing performance in a progressive manner by reconnecting partitioned networks through dispatched UAV relays. Our proposed algorithm uses two types of UAVs: global and local UAVs to collaboratively find the best deployment position in a dynamically changing environment. To obtain terrestrial network connectivity information and extract high-level network topology, we exploit the concept of strongly connected component in graph theory. Based on the understanding from a global point view, global UAVs recommend the most effective deployment positions to local UAVs so that they are deployed as relays in more critically disrupted areas. Simulation-based experiments validate that our distributed route reconstruction algorithm outperforms a counterpart algorithm in terms of steady-state and dynamic routing performance.
AB - In this paper, we address a route reconstruction problem using Unmanned Aerial Vehicles (UAVs) after a large-scale disaster where stationary ad-hoc networks are severely destructed. The main goal of this paper is to improve routing performance in a progressive manner by reconnecting partitioned networks through dispatched UAV relays. Our proposed algorithm uses two types of UAVs: global and local UAVs to collaboratively find the best deployment position in a dynamically changing environment. To obtain terrestrial network connectivity information and extract high-level network topology, we exploit the concept of strongly connected component in graph theory. Based on the understanding from a global point view, global UAVs recommend the most effective deployment positions to local UAVs so that they are deployed as relays in more critically disrupted areas. Simulation-based experiments validate that our distributed route reconstruction algorithm outperforms a counterpart algorithm in terms of steady-state and dynamic routing performance.
UR - http://www.scopus.com/inward/record.url?scp=85049221569&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2018.8377012
DO - 10.1109/WCNC.2018.8377012
M3 - Conference contribution
AN - SCOPUS:85049221569
T3 - IEEE Wireless Communications and Networking Conference, WCNC
SP - 1
EP - 6
BT - 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 15 April 2018 through 18 April 2018
ER -