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Development of efficient fault tolerant storage and processing for multidimensional graphics data for information control systems

Keywords:

A. N. Kokoulin – Ph.D. (Eng.), Associate Professor, Perm National Research Polytechnic University. E-mail: liga_asu@mail.ru


This paper describes an approach that leverages the functionality of LH*RS – distributed data storage concept [1, 2]. LH*RS is a high-availability scalable distributed data structure (SDDS). The invented LH*RS is positioned as the general-purpose method, and its efficiency does not depend on the data file type. We can analyse the way to optimize its performance characteristics, in particular for the case of imagery data. There are two main issues that appear with image files visualization and exchange: processing large images, for example high-resolution astronomy and geospatial image coverings; рrocessing requests for multiple copies of a single image with distinct scale and resolution, for example, web-site pictures having thumbnail, medium and high-resolution quality images stored separately. A new result of the paper is suggested approach to build distributed fault-tolerant storage system of imagery data. Developed storage schema contains the sole copy of imagery data at highest resolution and scale. Image is decomposed into data blocks of several levels. The image with the required scale and resolution is reconstructed from the corresponding set of downloaded blocks on client’s side. The developed method allows adopting the encoding and compression algorithms usage and algorithm redundancy on the block level. Thereby we can flexibly manage the redundancy, security permissions and resource consumption.
References:

  1. Petrov V.A. Modelirovanie perenosa i poiska danny'x v deczentralizovannoj raspredelennoj sisteme, ispol'zuyushhej N–k-sxemu xraneniya informaczii. Diss. k.f.-m.n. 05.13.18. M.: 2008. 112 s.
  2. Litwin W., Moussa R., Schwarz T.J.E. LH*RS: a highly available distributed data storage. http://portal.acm.org/cita­tion.cfm?id=1316816
  3. Chilingarian I., Bartunov O., Richter J., Sigaev T. PostgreSQL: the Suitable DBMS Solution for Astronomy and Astro­physics / ASP Conference Series. V. 314. Astronomical Data Analysis Software and Systems XIII. P. 225.
  4. Bartunov O.S., Samodurov V.A. Astronomiya i internet: istoriya vzaimootnoshenij / Zemlya i Vselennaya. 2000. № 1. S. 49–59.

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