On Coverage and Capacity for Disaster Area Wireless Networks Using Mobile Relays

<p/> <p>Public safety organizations increasingly rely on wireless technology to provide effective communications during emergency and disaster response operations. This paper presents a comprehensive study on dynamic placement of relay nodes (RNs) in a disaster area wireless network. It...

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Main Authors: Guo Wenxuan, Huang Xinming
Format: Article
Language:English
Published: SpringerOpen 2009-01-01
Series:EURASIP Journal on Wireless Communications and Networking
Online Access:http://jwcn.eurasipjournals.com/content/2009/251314
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spelling doaj-0fefe5a0f206429da2de8fd758e01b052020-11-24T23:52:32ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14721687-14992009-01-0120091251314On Coverage and Capacity for Disaster Area Wireless Networks Using Mobile RelaysGuo WenxuanHuang Xinming<p/> <p>Public safety organizations increasingly rely on wireless technology to provide effective communications during emergency and disaster response operations. This paper presents a comprehensive study on dynamic placement of relay nodes (RNs) in a disaster area wireless network. It is based on our prior work of mobility model that characterizes the spatial movement of the first responders as mobile nodes (MNs) during their operations. We first investigate the COverage-oriented Relay Placement (CORP) problem that is to maximize the total number of MNs connected with the relays. Considering the network throughput, we then study the CApacity-oriented Relay Placement (CARP) problem that is to maximize the aggregated data rate of all MNs. For both coverage and capacity studies, we provide each the optimal and the greedy algorithms with computational complexity analysis. Furthermore, simulation results are presented to compare the performance between the greedy and the optimal solutions for the CORP and CARP problems, respectively. It is shown that the greedy algorithms can achieve near optimal performance but at significantly lower computational complexity.</p>http://jwcn.eurasipjournals.com/content/2009/251314
collection DOAJ
language English
format Article
sources DOAJ
author Guo Wenxuan
Huang Xinming
spellingShingle Guo Wenxuan
Huang Xinming
On Coverage and Capacity for Disaster Area Wireless Networks Using Mobile Relays
EURASIP Journal on Wireless Communications and Networking
author_facet Guo Wenxuan
Huang Xinming
author_sort Guo Wenxuan
title On Coverage and Capacity for Disaster Area Wireless Networks Using Mobile Relays
title_short On Coverage and Capacity for Disaster Area Wireless Networks Using Mobile Relays
title_full On Coverage and Capacity for Disaster Area Wireless Networks Using Mobile Relays
title_fullStr On Coverage and Capacity for Disaster Area Wireless Networks Using Mobile Relays
title_full_unstemmed On Coverage and Capacity for Disaster Area Wireless Networks Using Mobile Relays
title_sort on coverage and capacity for disaster area wireless networks using mobile relays
publisher SpringerOpen
series EURASIP Journal on Wireless Communications and Networking
issn 1687-1472
1687-1499
publishDate 2009-01-01
description <p/> <p>Public safety organizations increasingly rely on wireless technology to provide effective communications during emergency and disaster response operations. This paper presents a comprehensive study on dynamic placement of relay nodes (RNs) in a disaster area wireless network. It is based on our prior work of mobility model that characterizes the spatial movement of the first responders as mobile nodes (MNs) during their operations. We first investigate the COverage-oriented Relay Placement (CORP) problem that is to maximize the total number of MNs connected with the relays. Considering the network throughput, we then study the CApacity-oriented Relay Placement (CARP) problem that is to maximize the aggregated data rate of all MNs. For both coverage and capacity studies, we provide each the optimal and the greedy algorithms with computational complexity analysis. Furthermore, simulation results are presented to compare the performance between the greedy and the optimal solutions for the CORP and CARP problems, respectively. It is shown that the greedy algorithms can achieve near optimal performance but at significantly lower computational complexity.</p>
url http://jwcn.eurasipjournals.com/content/2009/251314
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