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Multi-node Approach for Map Data Processing

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Advanced Computing and Systems for Security

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 897))

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Abstract

OpenStreetMap (OSM) is a popular collaborative open-source project that offers free editable map across the whole world. However, this data often needs a further on-purpose processing to become the utmost valuable information to work with. That is why the main motivation of this paper is to propose a design for big data processing along with data mining leading to the obtaining of statistics with a focus on the detail of a traffic data as a result in order to create graphs representing a road network. To ensure our High-Performance Computing (HPC) platform routing algorithms work correctly, it is absolutely essential to prepare OSM data to be useful and applicable for above-mentioned graph, and to store this persistent data in both spatial database and HDF5 format.

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Notes

  1. 1.

    Extract, transform, load process.

  2. 2.

    Volunteered Geographic Information.

  3. 3.

    For example based on road classification and number of lanes.

  4. 4.

    That is forcing our changes locally; correcting road information from OSM dataset.

References

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  12. Protocol Buffers. https://github.com/google/protobuf/

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Acknowledgements

This work has been partially funded by ANTAREX, a project supported by the EU H2020 FET-HPC program under grant 671623, by The Ministry of Education, Youth and Sports of the Czech Republic from the National Programme of Sustainability (NPU II) project ‘IT4 Innovations excellence in science—LQ1602’.

Author information

Authors and Affiliations

  1. IT4Innovations National Supercomputing Center, VŠB - Technical University of Ostrava, Ostrava, Czech Republic

    Vít Ptošek & Kateřina Slaninová

Authors
  1. Vít Ptošek
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  2. Kateřina Slaninová
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Corresponding author

Correspondence to Vít Ptošek .

Editor information

Editors and Affiliations

  1. A.K. Choudhury School of Information Technology, University of Calcutta, Kolkata, West Bengal, India

    Rituparna Chaki

  2. Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca’ Foscari Venezia, Mestre, Venice, Italy

    Agostino Cortesi

  3. Faculty of Computer Science, Bialystok University of Technology, Bialystok, Poland

    Khalid Saeed

  4. Department of Computer Science and Engineering, University of Calcutta, Kolkata, West Bengal, India

    Nabendu Chaki

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Ptošek, V., Slaninová, K. (2019). Multi-node Approach for Map Data Processing. In: Chaki, R., Cortesi, A., Saeed, K., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 897. Springer, Singapore. https://doi.org/10.1007/978-981-13-3250-0_7

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