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.
National Science Foundation, Division of Computer and Network Systems