Two-Stage Framework for Big Spatial Data Analytics to Support Disaster Response

Xuan Hu, Jie Gong, Eduard Gibert Renard, Manish Parashar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

During disaster response, large volumes and diverse types of data sets are often continuously generated, and in many case these data sets create overwhelming burdens to data processing infrastructure and teams. At the same time, decision making during disaster response requires timely and relevant information which has to be extracted as expeditiously as possible from these large data sets. Therefore, processing of disaster related data sets is often time sensitive and requires coordination and prioritization. To accomplish this, we propose a two-stage approach to facilitate efficient and effective data processing for disaster decision support. In the first stage, a Data Envelope Analysis (DEA) model is introduced to model the articulation process about information needs such that providing a formal way of prioritizing data processing task. In the second stage, the prioritized data processing workflow is implemented on an Apache Storm based streaming processing platform in the EC2 cloud, with a focus on computational resource optimization. To validate the proposed approach, a Hurricane Sandy based use case was used to evaluate the performance of the proposed approach. Results show that our approach can compute up to 69% (three supervisor nodes) faster than a conventional serial processing approach.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
EditorsChaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5409-5418
Number of pages10
ISBN (Electronic)9781728108582
DOIs
StatePublished - Dec 2019
Event2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States
Duration: Dec 9 2019Dec 12 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

Conference

Conference2019 IEEE International Conference on Big Data, Big Data 2019
Country/TerritoryUnited States
CityLos Angeles
Period12/9/1912/12/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

Keywords

  • Big Spatial Data
  • Decision Support
  • Disaster Response
  • Stream Processing

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