Publication detail

Algorithmization and Optimization of Processing of Big Geographical Data

BARTONĚK, D. BUREŠ, J.

Original Title

Algorithmization and Optimization of Processing of Big Geographical Data

Type

journal article in Scopus

Language

English

Original Abstract

This paper presents the optimization of evaluation of large volume of geographic data. The core of the method is hierarchical decomposition of the set of processes into elementary processes and the allocation of means to these processes. The means can be of three types: hardware, software or human factor, eventually combination of these types. Each elementary process can be processed at one of these means in certain time. Generally, the processes and the means can be interdependent or independent. The described problem can be represented using an oriented graph, where nodes correspond to the processes or the means and edges represent either the interdependence of processes and means, or the processing time of certain process on a given mean. The map of processes is formed on the basis of the graph. This map contains temporal continuity of solutions of sub-processes. Then, the duration of all processes is compiled from this map, which must be less than the time solving a task in the required quality of results. If not, the pairs of sub process–mean are replaced alternative pairs according to the map of processes with lower duration. The special algorithm was designed for this task. If the sum of the durations of all processes complies with solutions, the optimization ends and at this time the sub-processes and their allocated means are defined. The proposed method of data processing was realized in the project of data analysis of storage of gas facilities under certain types of terrain surface in the Czech Republic with the area of 64,350 km2.

Keywords

algorithmization, process scheduling, optimization, GIS

Authors

BARTONĚK, D.; BUREŠ, J.

Released

1. 12. 2016

Publisher

American Scientific Publisher

Location

USA

ISBN

1546-1955

Periodical

Journal of Computational and Theoretical Nanoscience

Year of study

13

Number

12

State

United States of America

Pages from

9098

Pages to

9104

Pages count

7

URL

http://www.aspbs.com/ctn/

BibTex

@article{BUT132992,
  author="Dalibor {Bartoněk} and Jiří {Bureš}",
  title="Algorithmization and Optimization of Processing of Big Geographical Data",
  journal="Journal of Computational and Theoretical Nanoscience",
  year="2016",
  volume="13",
  number="12",
  pages="9098--9104",
  doi="10.1166/jctn.2016.6286",
  issn="1546-1955",
  url="http://www.aspbs.com/ctn/"
}