• Polymer(Korea)
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• v.32 no.1
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• pp.26-30
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• 2008

This study was designed to investigate the effect of hybridization of synthetic/natural materials for annulus fibrosus (AF) tissue regeneration in vitro and in vivo. The synthetic/natural hybrid scaffolds were prepared using PLGA (poly (lactic-co-glycolic) acid), SIS (small intestinal submucosa) and DBP (demineralized bone particles). PLGA, PLGA/SIS(20%), PLGA/DBP(20%) and PLGA/SIS (10%)/DBP (10%) scaffold were manufactured by solvent casting/salt leaching method. Compressive strength was measured. Rabbit AF cells were isolated, cultured and seeded into experimental groups. Hydroxyproline production and DNA quantity of AP cells on each scaffold was measured at 2, 4 and 6 weeks after in vitro culture. Cell-scaffold composites were implanted subcutaneously into athymic mice. After 1,4 and 6 weeks postoperatively, specimens were taken and H&E, Safranin-O and type I collagen staining were carried out concerning formation of cartilagenous tissue. In vitro PLGA/SIS scaffold was evaluated for total collagen content (bydroryproline/DNA content) and PLGA scaffold was evaluated for compressive strength.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.1
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• pp.26-32
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• 2009

The multi-level storage architecture has been widely adopted in servers and data centers. However, while prefetching has been shown as a crucial technique to exploit sequentiality in accesses common for such systems and hide the increasing relative cost of disk I/O, existing multi-level storage studies have focused mostly on cache replacement strategies. In this paper, we show that prefetching algorithms designed for single-level systems may have their limitations magnified when applied to multi-level systems. Overly conservative prefetching will not be able to effectively use the lower-level cache space, while overly aggressive prefetching will be compounded across levels and generate large amounts of wasted prefetch. We design and implement a hierarchy-aware lower-level prefetching strategy called PMS(Prefetching strategy for Multi-level Storage system) that applicable to any upper level prefetching algorithms. PMS does not require any application hints, a priori knowledge from the application or modification to the va interface. Instead, it monitors the upper-level access patterns as well as the lower-level cache status, and dynamically adjusts the aggressiveness of the lower-level prefetching activities. We evaluated the PMS through extensive simulation studies using a verified multi-level storage simulator, an accurate disk simulator, and access traces with different access patterns. Our results indicate that PMS dynamically controls aggressiveness of lower-level prefetching in reaction to multiple system and workload parameters, improving the overall system performance in all 32 test cases. Working with four well-known existing prefetching algorithms adopted in real systems, PMS obtains an improvement of up to 35% for the average request response time, with an average improvement of 16.56% over all cases.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.455-462
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• 2006

Recently, the filtering approach using vector approximation such as VA-file[1] or LPC-file[2] have been proposed to support similarity search in high dimensional data space. This approach filters out many irrelevant vectors by calculating the approximate distance from a query vector using the compact approximations of vectors in database. Accordingly, the total elapsed time for similarity search is reduced because the disk I/O time is eliminated by reading the compact approximations instead of original vectors. However, the search time of the VA-file or LPC-file is not much lessened compared to the brute-force search because it requires a lot of computations for calculating the approximate distance. This paper proposes a new bitmap index structure in order to minimize the calculating time. To improve the calculating speed, a specific value of an object is saved in a bit pattern that shows a spatial position of the feature vector on a data space, and the calculation for a distance between objects is performed by the XOR bit calculation that is much faster than the real vector calculation. According to the experiment, the method that this paper suggests has shortened the total searching time to the extent of about one fourth of the sequential searching time, and to the utmost two times of the existing methods by shortening the great deal of calculating time, although this method has a longer data reading time compared to the existing vector approximation based approach. Consequently, it can be confirmed that we can improve even more the searching performance by shortening the calculating time for filtering of the existing vector approximation methods when the database speed is fast enough.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2784-2790
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• 2015

The column-oriented database storage is a very advanced model for large-volume data transactions because of its superior I/O performance. Traditional data storages exploit row-oriented storage where the attributes of a record are placed contiguously in hard disk for fast write operations. However, for search-mostly data warehouse systems, column-oriented storage has become a more proper model because of its superior read performance. Recently, solid state drive using flash memory is largely recognized as the preferred storage media for high-speed data analysis systems. In this research, we propose a new transaction recovery scheme for a column-oriented database environment which is based on a flash media file system. We improved traditional shadow paging schemes by reusing old data pages which are supposed to be invalidated in the course of writing a new data page in the flash file system environment. In order to reuse these data pages, we exploit reused shadow list structure in our column-oriented shadow recovery(CoSR) scheme. CoSR scheme minimizes the additional storage overhead for keeping shadow pages and minimizes the I/O performance degradation caused by column data compression of traditional recovery schemes. Based on the results of the performance evaluation, we conclude that CoSR outperforms the traditional schemes by 17%.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.21-30
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• 2011

In the global IT market, a lot of issues for responding to various environmental regulations emerged. In case of the data centers, it is consuming huge amounts of energy to maintain. So there have been various technical attempts as Consolidation, Virtualization, Optimization to efficiently manage energy and data storage to fix the problems. In this paper, we propose a new RAID(Redundant Array of Independent Disks) mechanism which is differing the intensity of power consumption and works to provide data protection and disaster recovery(backup, mirroring etc.) to stratify multiple volumes. G-RAID minimize the power consumption and the lower of I/O performance by selecting the volume depending on the frequency of data access while classifying the power consumption between volumes in storage system. Also, it is possible that a filesystem and block map information of G-RAID is processed by basic unit which is group located in a row for the blocks to work efficiently and can minimize the performance degradation of block mapping load by the access frequency in each groups. As a result, we obtained to elevate a little bit of response time caused by block relocation work, but showed the decrease of power consumption by 38%.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.29-38
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• 2011

Unlike in traditional row-oriented database systems, a column-oriented database system stores data in column-oriented and not row-oriented order. Recently, research results revealed the effectiveness of column-oriented databases for applications such as data warehouse and decision support systems that access large volumes of data in a read only manner. In this paper, we investigate the join strategies for column-oriented databases and prove the effectiveness of column-oriented databases in data warehouse systems. For unbiased comparison, the two database systems are analyzed using the star schema benchmark and the performance analysis of a star schema join query is carried out. We experimented with well-known join algorithms and considered early materialization and late materialization join strategies for column-oriented databases. The performance results confirm that star schema join queries perform better in terms of disk I/O cost in column-oriented databases than in row-oriented databases. In addition, the late materialization strategy showed more performance gain than the early materialization strategy in column-oriented databases.

• The KIPS Transactions:PartD
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• v.18D no.3
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• pp.157-168
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• 2011

Recently flash memory has been being utilized as a main storage device in mobile devices, and flashSSDs are getting popularity as a major storage device in laptop and desktop computers, and even in enterprise-level server machines. Unlike HDDs, on flash memory, the overwrite operation is not able to be performed unless it is preceded by the erase operation to the same block. To address this, FTL(Flash memory Translation Layer) is employed on flash memory. Even though the modified data block is overwritten to the same logical address, FTL writes the updated data block to the different physical address from the previous one, mapping the logical address to the new physical address. This enables flash memory to avoid the high block-erase cost. A flashSSD has an array of NAND flash memory packages so it can access one or more flash memory packages in parallel at once. To take advantage of the internal parallelism of flashSSDs, it is beneficial for DBMSs to request I/O operations on sequential logical addresses. However, the B-tree structure, which is a representative index scheme of current relational DBMSs, produces excessive I/O operations in random order when its node structures are updated. Therefore, the original b-tree is not favorable to SSD. In this paper, we propose AS(Always Sequential) B-tree that writes the updated node contiguously to the previously written node in the logical address for every update operation. In the experiments, AS B-tree enhanced 21% of B-tree's insertion performance.

• The KIPS Transactions:PartA
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• v.19A no.1
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• pp.35-44
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• 2012

Traditional technologies that are used to improve the performance of hard disk drives show many negative cases if they are applied to solid state drives (SSD). Access time and block sequence in hard disk drives that consist of mechanical components are very important performance factors. Meanwhile, SSD provides superior random read performance that is not affected by block address sequence due to the characteristics of flash memory. Practically, it is recommended to disable prefetching if a SSD is installed in a personal computer. However, this paper presents a combinational method of a prefetching scheme and a memory management that consider the internal structure of SSD and the characteristics of NAND flash memory. It is important that SSD must concurrently operate multiple flash memory chips. The I/O unit size of NAND flash memory tends to increase and it exceeded the block size of operating systems. Hence, the proposed prefetching scheme performs in an operating unit of SSD. To complement a weak point of the prefetching scheme, the proposed memory management scheme adaptively evicts uselessly prefetched data to maximize the sum of cache hit rate and prefetch hit rate. We implemented the proposed schemes as a Linux kernel module and evaluated them using a commercial SSD. The schemes improved the I/O performance up to 26% in a given experiment.

• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.51-62
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• 2004

Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries. To improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structures of GALIS architecture,which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.3
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• pp.324-336
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• 2000

The paper proposes an efficient buffer management scheme to enhance performance of the disk I/O system. Without any user level information, the proposed scheme automatically detects the block reference patterns of applications by associating block attributes with forward distance of a block. Based on the detected patterns, the scheme applies an appropriate replacement policy to each application. We also present a new block allocation scheme to improve the performance of buffer cache when kernel needs to allocate a cache block due to a cache miss. The allocation scheme analyzes the cache hit ratio of each application based on block reference patterns and allocates a cache block to maximize cache hit ratios of system. These all procedures are performed on-line, as well as automatically at system level. We evaluate the scheme by trace-driven simulation. Experimental results show that our scheme leads to significant improvements in hit ratios of cache blocks compared to the traditional schemes and requires low overhead.