DocumentCode :
578426
Title :
Group mobility model in disaster area networks
Author :
Shang, Xufeng ; Yuan, Yubo
Author_Institution :
Sch. of Sci., China Jiliang Univ., Hangzhou, China
Volume :
4
fYear :
2012
fDate :
15-17 July 2012
Firstpage :
1508
Lastpage :
1513
Abstract :
We present an improved random way-point with area and direction limitation mobility model (IRWPADL) to describe the movement patterns of the search groups. In the model, we adopt the side-by-side carpet searching on the purpose of searching the victims fairly and efficiently. Considering the assignment by the mobility model of Random Way Point with Fixed Access Point (RWPFAP) has low rescue efficiency and does not utilize the rescue manpower adequately, we modify the RWPFAP mobility model in terms of the group partitioning and merging. We devise the rescue groups´ simulated moving track of the two mobility models. By comparison with the two models on the average waiting time for rescue,we draw the conclusion that the modified model does have higher rescue efficiency. We further discuss the variation trend of the average waiting time for rescue caused by the fluctuation of the number of the rescue points and the average rescue duration.
Keywords :
disasters; emergency management; mobile computing; random processes; IRWPADL mobility model; RWPFAP mobility model; disaster area networks; group merging; group mobility model; group partitioning; improved random way-point with area and direction limitation mobility model; movement pattern; random way point with fixed access point; rescue group efficiency; rescue group simulated moving track; Abstracts; Educational institutions; Group Mobility Model; Random Way Point with Fixed Access Point; Side-by-side carpet searching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
ISSN :
2160-133X
Print_ISBN :
978-1-4673-1484-8
Type :
conf
DOI :
10.1109/ICMLC.2012.6359588
Filename :
6359588
Link To Document :
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