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Garay-Sianca, A., Nurre, S. G., Castro Salas, C. L., & Alvarez A., H. R. (2018). Data Processing on Large Interdependent Networks: An Application for Infrastructure Preparedness, and Restoration. KnE Engineering, 3(2), 458-468. https://doi.org/10.18502/keg.v3i1.1450

https://doi.org/10.18502/keg.v3i1.1450

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authors

  • Aniela Garay-Sianca

    Aniela Garay-Sianca

    University of Arkansas, Fayetteville, Arkansas
  • Sarah G. Nurre

    Sarah G. Nurre

    University of Arkansas, Fayetteville, Arkansas
  • C. L. Castro Salas

    C. L. Castro Salas

    Intel, Santa Clara, California
  • Humberto R. Alvarez A.

    Humberto R. Alvarez A.

    Technological University of Panama, Panama City

Published Date

  • Feb 11, 2018

Data Processing on Large Interdependent Networks: An Application for Infrastructure Preparedness, and Restoration

KnE Engineering / 6th Engineering, Science and Technology Conference - Panama 2017 (ESTEC 2017) / Pages 458-468

Abstract

This paper presents a method for validating and transforming data for use in interdependent infrastructure network analysis. Critical infrastructure are interdependent on each other for delivery of services and execution of restoration activities.  These interdependencies make infrastructure systems vulnerable to extreme events and highlights the needs for preparedness and response plans.  Optimization models have been used to create effective plans using interdependent infrastructure networks.  These models require accurate input data.  However, many data sources have inconsistencies or errors which inhibit the ability to use such optimization models.   This work identifies common errors in input network data and provides a method for processing and correcting these errors.  We demonstrate the effectiveness of this method on data representing the transportation network in Juan Diaz town, in Panama.

 

Keywords: Data processing, network, infrastructure, interdependence.

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