BDD: Disaster Preparation and Response via Big Data Analysis and Robust Networking

BDD：通过大数据分析和强大的网络进行灾难准备和响应

基本信息

批准号：
1461886
负责人：
Guoliang Xue
金额：
$ 30万
依托单位：
Arizona State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2015
资助国家：
美国
起止时间：
2015-04-01 至 2019-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1461886&HistoricalAwards=false
关键词：
BDD Disaster Preparation Response via

项目摘要

Disasters are events with dire consequences, requiring multiple-agency responses and resources beyond the capability of a single community. Natural disasters, such as the 2011 Great East Japan Earthquake, can threaten the lives of many people and cause inordinate economic losses. Communication is critical to disaster preparation, response, and recovery, but may be damaged during the disaster. In this project, researchers from the US and Japan study novel approaches to disaster preparation, response and recovery using survivable communication networks and big data analysis of social media data. This collaborative effort involves expertise in disaster research, social media mining and big data analysis, network science, wireless communications, and machine learning, to examine resilient network architecture and algorithms, data collection and analysis before the disaster, and decision making and information dissemination during the disaster. The resilient network incorporates both wired and wireless communications to deal with multiple disaster-induced failures, aiming for efficient algorithms serving emergency applications. State-of-the-art data collection and analysis techniques will help build an important knowledge base in proactive preparation for disasters. Real time decision making and information dissemination during a disaster can assist disaster response and recovery effectively. The proposed research aims to provide valuable guidance for disaster preparation, response, and recovery for both the US and Japan, and spearhead a new research direction in survivable communication network design and big data analysis. This project provides a conducive environment to further research collaboration of big data analysis and disaster relief between the US and Japan. Graduate students will be jointly trained in this international research project to actively collaborate in carrying out the proposed research tasks. Special efforts will be made to engage minority students and underrepresented groups.

灾难是带有可怕后果的事件，需要超出单个社区能力的多机构响应和资源。自然灾害，例如2011年东日本大地震，可能威胁着许多人的生命并造成过度的经济损失。沟通对于灾难准备，反应和恢复至关重要，但在灾难中可能会受到损害。在这个项目中，美国和日本的研究人员研究了使用可生存的通信网络以及社交媒体数据的大数据分析的灾难准备，反应和恢复方法。这项协作工作涉及灾难研究，社交媒体挖掘和大数据分析，网络科学，无线通信和机器学习方面的专业知识，以检查灾难前的弹性网络架构和算法，数据收集和分析以及灾难期间的决策和信息传播。弹性网络将有线和无线通信结合在一起，以处理多个灾难引起的故障，旨在有效地服务紧急应用程序。最先进的数据收集和分析技术将有助于在积极准备灾难的准备方面建立重要的知识库。灾难期间的实时决策和信息传播可以有效地帮助灾难反应和康复。拟议的研究旨在为美国和日本提供灾难准备，反应和恢复的宝贵指导，并为生存的通信网络设计和大数据分析带来新的研究方向。该项目提供了一个有利的环境，以进一步研究美国和日本之间大数据分析和救灾的合作。研究生将在该国际研究项目中共同培训，以积极合作执行拟议的研究任务。将要做出特别的努力，以吸引少数族裔学生和代表性不足的团体。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Load Balancing for Interdependent IoT Microservices

DOI：
10.1109/infocom.2019.8737450
发表时间：
2019-04
期刊：
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications
影响因子：
0
作者：
Ruozhou Yu;Vishnu Teja Kilari;G. Xue;Dejun Yang
通讯作者：
Ruozhou Yu;Vishnu Teja Kilari;G. Xue;Dejun Yang

Application Provisioning in Fog Computing-enabled Internet-of-Things: A Network Perspective

DOI：
10.1109/infocom.2018.8486269
发表时间：
2018-01-01
期刊：
IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2018)
影响因子：
0
作者：
Yu, Ruozhou;Xue, Guoliang;Zhang, Xiang
通讯作者：
Zhang, Xiang

Capacity-aware cost-efficient network reconstruction for post-disaster scenario

DOI：
10.1109/pimrc.2016.7794910
发表时间：
2016-09
期刊：
2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)
影响因子：
0
作者：
Xiaoyan Wang;Hao Zhou;L. Zhong;Yusheng Ji;K. Takano;S. Yamada;G. Xue
通讯作者：
Xiaoyan Wang;Hao Zhou;L. Zhong;Yusheng Ji;K. Takano;S. Yamada;G. Xue

Population-Aware Relay Placement for Wireless Multi-Hop Based Network Disaster Recovery