• Journal of KIISE:Computer Systems and Theory
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• v.33 no.8
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• pp.547-553
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• 2006

We present a new geometry coding method for 3D meshes, an adaptive subdivision. Previous localized geometry coding methods have demonstrated better compression ratios than the global approach but they are considered hard to use in practice partly due to time - consuming quantization. Our new localized scheme replaces this quantization with an adaptive subdivision of the localized range. The deeper level a user chooses, the closer to the original the mesh will be restored. We also present an improved connectivity coder upon the current leading Angle-Analyzer's by applying a context-modeling. As a result, our new coder provides reliable and intuitive controls between bit-rate and distortion without losing efficiency.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.4
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• pp.32-39
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• 1999

Video-On-Demand servers have to provide timely processing guarantees and reduce the storage and reduce the storage and bandwidth requirements for continuous media However, compression techniques used in Video-On-Demand servers make the bit rates of compressed video data significantly variable from frame to frame Consequently, most pervious Video-On-Demand servers which use constant bit rate retrieval to guarantee deterministic service under-utilize the system resources and restrict the number of clients. In this paper, I propose a buffer management scheme called CAP(Caching And Prefetching) for Video-On-Demand server using variable bit rate continuous media. By caching and prefetching the data CAP reduces the variation of the compressed data and increases the number of clients simultaneously served and maximizes the utilization of system resources. Results of trace-driven simulations show the effectiveness of the scheme.

• Journal of KIISE:Information Networking
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• v.35 no.4
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• pp.318-325
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• 2008

Most of the sensor applications collect and analyze sensor data within a given period of time. When sensor send a data to sink, it spend many communication cost. Accordingly, a compression algorithm is one of the most critical issues for the communication cost decrease in sensor fields. In this paper, we propose an algorithm for compressing sensor data using the dynamic bit assignment technique. In our algorithm, sink collect sensor data within a short period of time and make bit assign information. Then sink send the information to sensor. Finally, sensors compresssensing data and send to sink.

• Journal of KIISE:Databases
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• v.32 no.4
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• pp.441-451
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• 2005

HTML is mostly stored in native file systems instead of specialized repositories such as a database. Like HTML, XML, the standard for the exchange and the representation of data in the Internet, is mostly resident on native file systems. However. since XML data is irregular and verbose, the disk space and the network bandwidth are wasted compared to those of regularly structured data. To overcome this inefficiency of XML data, the research on the compression of XML data has been conducted. Among recently proposed XML compression techniques, some techniques do not support querying compressed data, while other techniques which support querying compressed data blindly encode data values using predefined encoding methods without considering the types of data values which necessitates partial decompression for processing range queries. As a result, the query performance on compressed XML data is degraded. Thus, this research proposes an XML compression technique which supports direct and efficient evaluations of queries on compressed XML data. This XML compression technique adopts an encoding method, called dictionary encoding, to encode each tag of XML data and applies proper encoding methods for encoding data values according to the inferred types of data values. Also, through the implementation and the performance evaluation of the XML compression technique proposed in this research, it is shown that the implemented XML compressor efficiently compresses real-life XML data lets and achieves significant improvements on query performance for compressed XML data.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.646-661
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• 2003

It is not easy that we visualize the large volume data stored in the every client computers of the web environment. One solution is as follows. First we compress volume data, second store that in the database server, third transfer that to client computer, fourth visualize that with direct-volume-rendering in the client computer. In this case, we usually use wavelet transform for compressing large data. This paper reports the experiments for acquiring the wavelet bases and the compression ratios fit for the above processing paradigm. In this experiments, we compress the volume data Engine, CThead, Bentum into 50%, 10%, 5%, 1%, 0.1%, 0.03% of the total data respectively using Harr, Daubechies4, Daubechies12 and Daubechies20 wavelets, then visualize that with direct-volume-rendering, afterwards evaluate the images with eyes and image comparison metrics. When compression ratio being low the performance of Harr wavelet is better than the performance of the other wavelets, when compression ratio being high the performance of Daubechies4 and Daubechies12 is better than the performance of the other wavelets. When measuring with eyes the good compression ratio is about 1% of all the data, when measuring with image comparison metrics, the good compression ratio is about 5-10% of all the data.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.429-437
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• 2003

Over the last decades, improvements in CPU speed have greatly exceeded those in memory and disk speeds by orders of magnitude and this enabled the use of compression techniques to reduce the database size as well as the query cost. Although compression techniques are employed in various database researches, there is little work on compressing multi-dimensional index structures. In this paper, we propose an efficient compression method called the hybrid encoding method (HEM) that is tailored to multi-dimensional indexing structures. The HEM compression significantly reduces the query cost and the size of multi-dimensional index structures. Through mathematical analyses and extensive experiments, we show that the HEM compression outperforms an existing method in terms of the index size and the query cost.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.73-75
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• 2004

최근에 무선 인터넷과 이동 컴퓨팅 기술이 발전하고, 휴대 전화, PDA와 같은 이동 단말기가 보편화됨에 따라 사용자의 위치 정보를 활용하는 위치 기반 서비스(LBS: Location Based Service)가 다양한 분야에서 제공되고 있다. 모바일 환경에서 위치 기반 서비스를 제공하기 위해서는 모바일 장치에서 대용량의 공간 데이타를 신속하게 처리하고 효과적으로 관리하기 위한 공간 MMDBMS(Main Memory Database Management System)가 필요하다. 이에 본 논문에서는 기존의 PC용 MMDBMS인 HSQLDB를 확장하여 모바일 장치에서 공간 데이타를 효율적으로 관리할 수 있는 공간 MMDBMS를 설계 및 구현하였다. 공간 MMDBMS는 OGC의 공간 데이타 모델을 따르며, 공간 데이타 특성에 적합한 압축 기법인 산술 코딩 기법을 제공하고, 모바일 장치에 적합한 MBR 압축 및 해슁 기법을 이용한 공간 인덱스를 지원한다. 그리고, 모바일 장치의 낮은 성능의 프로세서에서 공간 데이타 디스플레이 기능을 제공하고, 모바일 장치와 디스크 기반 GIS인 ZEUS 사이에서 공간 데이타 import/export의 성능 향상을 위한 데이타 캐쉬 기능을 지원한다.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.4
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• pp.177-185
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• 2005

NAND-type flash memory is becoming increasingly popular as a large data storage for mobile computing devices. Since flash memory is an order of magnitude more expensive than magnetic disks, data compression can be effectively used in managing flash memory based storage systems. However, compressed data management in NAND-type flash memory is challenging because it supports only page-based I/Os. For example, when the size of compressed data is smaller than the page size. internal fragmentation occurs and this degrades the effectiveness of compression seriously. In this paper, we present an efficient flash compression layer (FCL) for NAND-type flash memory which stores several small compressed pages into one physical page by using a write buffer Based on prototype implementation and simulation studies, we show that the proposed scheme offers the storage of flash memory more than $140\%$ of its original size and expands the write bandwidth significantly.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.459-462
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• 2013

본 논문은 데이터 압축 효율 향상을 위하여 데이터에 대해서 무조건적인 압축을 시행하는 것이 아니라 SDD 알고리즘을 제시하고 범용데이타에 대한 압축을 수행한다. SDD 알고리즘은 범용 데이터 특성을 우선적으로 분석하여 압축 여부를 판단하게 된다. 이렇게 함으로써 압축 효율이 좋지 않은 경우에 대한 회피를 통해서 불필요한 압축을 하지 않을 수 있도록 한다. 불필요한 연산을 줄임으로써 압축 알고리즘의 성능 향상을 꾀할 수 있다. 특히, 이미 압축 알고리즘이 적용이 된 데이타의 경우에 압축 알고리즘을 재차 적용하더라도 효율적인 압축이 되지 않는 경우가 많다. 이러한 경우에도 불필요한 압축을 하지 않도록 한다. 본 논문에서 제안하는 기능에 대해 실제 구현하고, 구현된 내용에 대해서 실험을 수행하였다. 본 논문에서 제시한 내용에 대해서 실험한 결과 정상적인 동작이 됨을 확인할 수 있었다.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.83-87
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• 1995

The implementation of the voice dodec is imjplemented by using TMS320C30, which is the floating point DSP chip from Texas Instrument. QCELP (Qualcomm Code Excited Linear Prediction) is used to encode and decode the voice. The QCELP code is implemented by the TMS320C30 C-dode. The DSP board is controlled by the PC. The PC program tranfors the voice file from and to the DSP board, which is also implemented by C-code. The voice is encoded by the DSP board and the encoded data is transferred to PC to be stored as a file. To hear the voice. the voice data file is sent to DSP board and decoded to synthesize audible voice. Two flags are used by both programs to notify the status of the operation. By checking the flags, DSP and PC decides when the voice data is transferred between them.