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Optimization of HDF5 Performance for Virtual Reality Objects Enhanced by Implicit Features

Authors:
Alexander Tzokev
Angel Bachvarov
Stoyan Maleshkov

Keywords: Virtual Reality; HDF5; Data Chunking; Chunk Size Prediction; Databases.

Abstract:
The amount of data used in Virtual Reality environments can be very large especially when working on real-world engineering problems. The interaction between the environment and the user or enhancement the objects therein with implicit features require integration of a high performance data management system which allows an efficient data handling. The deployment of specialized scientific databases such as Hierarchical Data Format 5 (HDF5) offers certain advantages over more business-oriented relational database management systems. This paper presents results from a study for optimization of the storage efficiency of the HDF5 data base trough chunked datasets enabling effective handling of the large data amounts produced within and for virtual reality environments. Further, a method for predicting the optimal chunk size or arrays of native data types with rank 1 and 2 is discussed.

Pages: 48 to 54

Copyright: Copyright (c) IARIA, 2014

Publication date: February 23, 2014

Published in: conference

ISSN: 2308-4243

ISBN: 978-1-61208-319-3

Location: Nice, France

Dates: from February 23, 2014 to February 27, 2014