Reliability Analysis using Hadoop and MapReduce

Project Information

Discipline
Statistics (403) 
Subdiscipline
14.02 Aerospace, Aeronautical, and Astronautical Engineering 
Orientation
Research 
Abstract

Researchers can now analyze massive databases that were previously too cumbersome, inconsistent or irregular to drive high-quality output. The goal of this project is to first understand cloud platform infrastructures and then to investigate the use of cloud-computing and Big Data analytics to analyze data-intensive applications.

Intellectual Merit

This research will investigate the use of Hadoop and MapReduce database on performing reliability analysis on aerospace applications. The resulting material and results will be made available.

Broader Impacts

This research will provide an introduction to applying reliability analysis techniques to Big Data. Reliability analysis is an essential component of examining manufacturing processes/systems and computing power and efficiency will be essential for the analyses. The research results will be made to make available to FutureGrid.

Project Contact

Project Lead
Carl Walasek (carlwala) 
Project Manager
Carl Walasek (carlwala) 
Project Members
Jay Greenberg  

Resource Requirements

Hardware Systems
  • alamo (Dell optiplex at TACC)
  • foxtrot (IBM iDataPlex at UF)
  • hotel (IBM iDataPlex at U Chicago)
  • india (IBM iDataPlex at IU)
  • sierra (IBM iDataPlex at SDSC)
 
Use of FutureGrid

This research will investigate the use of Hadoop and MapReduce on performing reliability analysis on aerospace applications.

Scale of Use

A few VMs for each aerospace application. The project will have around 5 collaborators.

Project Timeline

Submitted
10/15/2013 - 16:45 
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