Big Data Analytics for Emergency Communication Networks: A Survey

被引:61
|
作者
Wang, Junbo [1 ]
Wu, Yilang [1 ]
Yen, Neil [1 ]
Guo, Song [1 ]
Cheng, Zixue [1 ]
机构
[1] Univ Aizu, Grad Sch Comp Sci & Engn, Aizu Wakamatsu, Fukushima 9658580, Japan
来源
关键词
Emergency communication networks; Big data analytics; Content analytics; Spatial analytics; Machine learning; SPATIAL ASSOCIATION; PREDICTION; CLASSIFICATION; CHALLENGES; SYSTEM; DELAY;
D O I
10.1109/COMST.2016.2540004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Disaster management is a crucial and urgent research issue. Emergency communication networks (ECNs) provide fundamental functions for disaster management, because communication service is generally unavailable due to large-scale damage and restrictions in communication services. Considering the features of a disaster (e.g., limited resources and dynamic changing of environment), it is always a key problem to use limited resources effectively to provide the best communication services. Big data analytics in the disaster area provides possible solutions to understand the situations happening in disaster areas, so that limited resources can be optimally deployed based on the analysis results. In this paper, we survey existing ECNs and big data analytics from both the content and the spatial points of view. From the content point of view, we survey existing data mining and analysis techniques, and further survey and analyze applications and the possibilities to enhance ECNs. From the spatial point of view, we survey and discuss the most popular methods and further discuss the possibility to enhance ECNs. Finally, we highlight the remaining challenging problems after a systematic survey and studies of the possibilities.
引用
收藏
页码:1758 / 1778
页数:21
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