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Efficient Test Data Compression for SoC through ASRL with Improved Dictionary based Compression Technique
S. Anandhi1, R. Neela2, M. Janaki Rani3

1S.Anandhi, Research Scholar, Electrical Engineering Department, Annamalai University, Chidambaram, India.
2R. Neela, Professor, Electrical Engineering Department, Annamalai University, Chidambaram, India.
3M. Janaki Rani, Professor, Electronics and Communication Engineering Department, Dr.M.G.R. Educational and Research Institute, Chennai, India.

Manuscript received on 25 August 2019. | Revised Manuscript received on 06 September 2019. | Manuscript published on 30 September 2019. | PP: 3591-3597 | Volume-8 Issue-11, September 2019. | Retrieval Number: K24780981119/2019©BEIESP | DOI: 10.35940/ijitee.K2478.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Data compression techniques are explored in this paper, through which system memory size gets reduced in an effective manner. The size of the memory is always a key constraint in the embedded system. Larger memory size increases the bandwidth utilization which raises the cost of hardware and data transmission. It is difficult to transfer large data through the network. Data compression encoding technique is utilized to minimize the data size. The redundant character is reduced or encoding the bits in data is done to reduce the data size. The proposed system focused on lossless compression where the original information of the data is available even though the data size is compressed. The data compression is done through a dictionary-based compression algorithm and Alternating Statistical Run Length code (ASRL). In the existing system of ASRL, the compression ratio is about 65.16% and 67.18% for two benchmark circuits S5378 &S9234. The compression ratio of the test data is increased by combining the ASRL and Improved Dictionary-Based compression Technique. The proposed combined technique provides 80.25%& 82.5% compression ratio for two benchmark circuits S5378 &S9234. This reduces the power dissipation problem in the circuit and thereby the area of the circuit gets reduced.
Keywords: Improved Dictionary Based compression Technique, ASRL, ALE, UML.
Scope of the Article: Energy Efficient Building Technology