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Performance analysis of data compression algorithms for heterogeneous architecture through parallel approach

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Abstract

Today, there is a huge demand for data compression due to the need to reduce the transmission time and increase the capacity of data storage. Data compression is a technique which represents an information, images, video files in a compressed or in a compact format. There are various data compression techniques which keep information as accurately as possible with the fewest number of bits and send it through communication channel. Arithmetic algorithm, Lempel–Ziv 77 (LZ77) and run length encoding with a K-precision (K-RLE) algorithms are lossless data compression algorithms which have lower performance rate because of their processing complexity as well as execution time. This paper presents an efficient parallel approach to reduce execution time for compression algorithms. The proposed OpenMP is an efficient tool for programming within parallel shared-memory environments. Finally, it shows that performance parallel model experimented using Open Multi-Processing (OpenMP) Application Programming Interface through Intel Parallel studio on multicore architecture platform with spec of Core 2 duo—2.4 GHz, 1 Gb RAM machine of parallel approach for compression algorithms has been improved remarkably against sequential approach. The improvement in compression ratio through an efficient parallel approach leads to reduction on transmission cost, reduction in storage space and bandwidth without additional hardware infrastructure. An overall performance evaluation shows arithmetic data compression algorithm with 46% which is better than LZ77 of 44% as well as K-RLE of 37% data compression algorithms.

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References

  1. Norcen R, Uhl A (2005) High performance JPEG 2000 and MPEG-4 VTC on SMPs using OpenMP. Parallel Comput 31(10-12):1082–1098

    Article  Google Scholar 

  2. Capo-Chichi, EP, Guyennet H, Friedt J-M (2009) K-RLE: a new data compression algorithm for wireless sensor network. In: Third international conference on sensor technologies and applications, 2009, SENSORCOMM’09. IEEE

  3. Mehboob R, Khan SA, Ahmed Z (2006) High speed lossless data compression architecture. In: Proceedings of IEEE international confrence on Multitopic, pp 84–88

  4. Choong F et al. (2006) Design and implementation of a data compression scheme: a partial matching approach. In: 2006 international conference on computer graphics, imaging and visualisation. IEEE

  5. Lonardi S, Szpankowski W (2003) Joint source-channel LZ’77 coding. In: Data compression conference, 2003, Proceedings, DCC 2003. IEEE

  6. Rashid M, Picard D, Pottier B (2008) Application analysis for parallel processing. In: 11th EUROMICRO conference on digital system design architectures, methods and tools, 2008, DSD’08. IEEE

  7. De Agostino S (2001) Parallelism and dictionary based data compression. Inf Sci 135(1–2):43–56

    Article  MathSciNet  Google Scholar 

  8. Trein J et al. (2008) A hardware implementation of a run length encoding compression algorithm with parallel inputs, pp 337–342

  9. Jang J et al. (2008) Variable-length block nine-coded compression technique with Huffman codes and symbol merging. In: SoC design conference, 2008. ISOCC’08, International, vol 1. IEEE

  10. Soyjaudah KMS et al. (2002) Higher order adaptive arithmetic coding using the prediction by partial match algorithm. In: Africon Conference in Africa, 2002, IEEE AFRICON, 6th vol 1. IEEE

  11. Kawabata T (2008) Enumerative implementation of Lempel–Ziv 77 algorithm. In: IEEE international symposium on information theory, 2008, ISIT 2008. IEEE. https://doi.org/10.1109/ISIT.2008.4595135

  12. Manchev N (2006) Parallel algorithm for run length encoding. In: Third international conference on information technology: new generations, 2006, ITNG 2006. IEEE

  13. Zeeh C (2003) The Lempel Ziv algorithm, pp 17

  14. Messom CH, Gupta GS, Demidenko SN (2007) Hough transform run length encoding for real-time image processing. IEEE Trans Instrum Meas 56(3):962–967

    Article  Google Scholar 

Download references

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Correspondence to V. Madhu Viswanatham.

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Mahammad, F.S., Viswanatham, V.M. Performance analysis of data compression algorithms for heterogeneous architecture through parallel approach. J Supercomput 76, 2275–2288 (2020). https://doi.org/10.1007/s11227-018-2478-3

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