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Parallel Processing of Images in Mobile Devices using BOINC

  • Mariela Curiel
  • , David F. Calle
  • , Alfredo S. Santamaría
  • , David F. Suarez
  • , Leonardo Flórez
  • Universidad Javeriana

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Medical image processing helps health professionals make decisions for the diagnosis and treatment of patients. Since some algorithms for processing images require substantial amounts of resources, one could take advantage of distributed or parallel computing. A mobile grid can be an adequate computing infrastructure for this problem. A mobile grid is a grid that includes mobile devices as resource providers. In a previous step of this research, we selected BOINC as the infrastructure to build our mobile grid. However, parallel processing of images in mobile devices poses at least two important challenges: the execution of standard libraries for processing images and obtaining adequate performance when compared to desktop computers grids. By the time we started our research, the use of BOINC in mobile devices also involved two issues: a) the execution of programs in mobile devices required to modify the code to insert calls to the BOINC API, and b) the division of the image among the mobile devices as well as its merging required additional code in some BOINC components. This article presents answers to these four challenges.

Original languageEnglish
Pages (from-to)87-101
Number of pages15
JournalOpen Engineering
Volume8
Issue number1
DOIs
StatePublished - 24 Feb 2018

Keywords

  • Android
  • ITK
  • grids
  • image processing
  • mobile devices
  • mobile grids
  • parallel processing

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