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D. L. Jones, K. Wagstaff, D. R. Thompson, L. D’Addario, R. Navarro, C. Mattmann, W. Majid, J. Lazio, R. Preston, and U. Rebbapragada, “Big Data Challenges for Large Radio Arrays,” IEEE Aerospace Conference, Big Sky, 3-10 March 2012, pp. 1-6.

has been cited by the following article:

• TITLE: Lossless Compression of SKA Data Sets

  AUTHORS: Karthik Rajeswaran, Simon Winberg

  KEYWORDS: Square; Kilometre; Array; Lossless; Compression; HDF5

  JOURNAL NAME: Communications and Network, Vol.5 No.4, November 28, 2013

  ABSTRACT: With the size of astronomical data archives continuing to increase at an enormous rate, the providers and end users of astronomical data sets will benefit from effective data compression techniques. This paper explores different lossless data compression techniques and aims to find an optimal compression algorithm to compress astronomical data obtained by the Square Kilometre Array (SKA), which are new and unique in the field of radio astronomy. It was required that the compressed data sets should be lossless and that they should be compressed while the data are being read. The project was carried out in conjunction with the SKA South Africa office. Data compression reduces the time taken and the bandwidth used when transferring files, and it can also reduce the costs involved with data storage. The SKA uses the Hierarchical Data Format (HDF5) to store the data collected from the radio telescopes, with the data used in this study ranging from 29 MB to 9 GB in size. The compression techniques investigated in this study include SZIP, GZIP, the LZF filter, LZ4 and the Fully Adaptive Prediction Error Coder (FAPEC). The algorithms and methods used to perform the compression tests are discussed and the results from the three phases of testing are presented, followed by a brief discussion on those results.