Performance Analysis in Web Based Data Uploading using LZ77 Compression and Chunking Method

Authors

  • Hadary Mallafi

DOI:

https://doi.org/10.21108/INDOJC.2016.1.1.8

Abstract

One of the limitations in data uploading process is the maximum request length, besides that the data size that us transferred is also an issue because it influences the data sending cost. One of the way to cope with the problem of maximum request length is by downsizing the file size (chunking). Another way to do it is by enlarging the maximum reques length. Downsizing the file size can be done by chunking the files into a smaller size or by compressing it. In this paper, the author conducted a research about the file compression process that is done in client server using the technology of AJAX and Webservice. In addition to that, the file compression is combined with file chunking. In this research, the compression method that is used is dictionary based i.e. Lempel Ziv 77(LZ77). This compression is used since it can be performed in AJAX. The analysis that is made by the researcher about the compression ratio, data sending process speed, compression time, decompression time, the compression method capability in handling the maximum request length and the combination method of compression and chunking in uploading process.  The result of this research shows that compression method can handle the maximum requet length. Based on the experiment conducted, the relations between the compression ratio and window length is positively corelated. It means that the greater the window length is the more the compression ratio is.  Meanwhile, the relation between window length and uploading time is negatively linearly corelated. It means that the greater the window length is the faster the uploading time is. In addition, it can also be observed that the relation between the decompression and the file size is positively linearly correlated. It means that the greater the file size is the more time needed for decompression is.

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References

Adiwijaya, Maharani, M., Dewi, B.K., Yulianto, F.A. and Purnama, B., 2013. digital image compression using graph coloring quantization based on wavelet-SVD. In Journal of Physics: Conference Series (Vol. 423, No. 1, p. 012019). IOP Publishing. [crossref]

Asleson, R. and Nathaniel, T., 2006. Schutta Foundations of Ajax.

Kim, D., Song, S. and Choi, B.Y., 2013, November. SAFE: Structure-aware file and email deduplication for cloud-based storage systems. In Cloud Networking (CloudNet), 2013 IEEE 2nd International Conference on (pp. 130-137). IEEE. [crossref]

Rigler, S., Bishop, W. and Kennings, A., 2007, April. FPGA-based lossless data compression using Huffman and LZ77 algorithms. In Electrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on (pp. 1235-1238). IEEE.[crossref]

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Published

2016-03-31

How to Cite

Mallafi, H. (2016). Performance Analysis in Web Based Data Uploading using LZ77 Compression and Chunking Method. Indonesian Journal on Computing (Indo-JC), 1(1), 37–48. https://doi.org/10.21108/INDOJC.2016.1.1.8

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Articles