• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.347-352
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• 2017

In this paper, we propose a method that reduces mobile user's handover call dropping probability by using cognitive radio technology(CR) in cellular - based wireless cognitive radio networks. The proposed method predicts a cell to visit by Ziv-Lempel algorithm, and then supports mobile user with prediction of spectrum holes based on CR technology when allocated channels are short in the cell. We make neural network predict spectrum hole resources, and make handover calls use the resources before initial calls. Simulation results show CR technology has the capability to reduce mobile user handover call dropping probability in cellular mobile communication networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4648-4663
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• 2020

This paper proposes the Lempel-Ziv 4(LZ4) compression accelerator optimized for scale-out servers in data centers. In order to reduce CPU loads caused by compression, we propose an accelerator solution and implement the accelerator on an Field Programmable Gate Array(FPGA) as heterogeneous computing. The LZ4 compression hardware accelerator is a fully pipelined architecture and applies 16 dictionaries to enhance the parallelism for high throughput compressor. Our hardware accelerator is based on the 20-stage pipeline and dictionary architecture, highly customized to LZ4 compression algorithm and parallel hardware implementation. Proposing dictionary architecture allows achieving high throughput by comparing input sequences in multiple dictionaries simultaneously compared to a single dictionary. The experimental results provide the high throughput with intensively optimized in the FPGA. Additionally, we compare our implementation to CPU implementation results of LZ4 to provide insights on FPGA-based data centers. The proposed accelerator achieves the compression throughput of 639MB/s with fine parallelism to be deployed into scale-out servers. This approach enables the low power Intel Atom processor to realize the Hadoop storage along with the compression accelerator.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.4
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• pp.75-82
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• 2004

The channel transmission ratio is speeded up by the combination of the Huffman algorithm, the model scheme of the lossy transform having minimum average code lengths for the image information and good instantaneous decoding capability, with the Lempel-Ziv algorithm showing the fast processing performance during the compression process. In order to increase the processing speed during the compression process, ICMEP algorithm is proposed and the entropy encoder of HDTV is designed and inspected. The ICMEP entropy encoder have been designed by choosing the top-down method and consisted of the source codes and the test benches by the behavior expression with VHDL. As a simulation results, implemented ICMEP entropy encoder confirmed that whole system efficiency by memory saturation prevention and compressibility increase improves.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.28-39
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• 2003

This paper is an overview of research contributions by the authors to the use of compression techniques to handle high resolution, multi-spectral images. Originally developed in the remote sensing context, the same techniques are here applied to food and medical images. The objective is to point out the potential of this kind of processing in different contexts such as remote sensing, food monitoring, and medical imaging and to stimulate new research exploitations. Compression is based on the simple assumption that it is possible to find out a relationship between pixels close one each other in multi-spectral images it translates to the possibility to say that there is a certain degree of correlation within pixels belonging to the same band in a close neighbourhood. Once found a correlation based on certain coefficient on one band, the coefficients of this relationship are, in turn, quite probably, similar to the ones calculated in one of the other bands. Based upon this second observation, an algorithm was developed, able to reduce the number of bit/pixel from 16 to 4 in satellite remote sensed multi-spectral images. A comparison is carried out between different methods about their speed and compression ratio. As reference it was taken the behaviour of three common algorithms, LZW (Lempel-Ziv-Welch), Huffman and RLE (Run Length Encoding), as they are used in common graphic format such as GIF, JPEG and PCX. The Presented methods have similar results in both speed and compression ratio to the commonly used programs and are to be preferred when the decompression must be carried out on line, inside a main program or when there is the need of a custom made compression algorithm.