• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.33-36
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• 2011

본 논문에서는 SMART(Self-Monitoring Analysis and Reporting Technology)를 기반으로 SSD(Solid State Drives) 저장 장치의 신뢰성을 분석할 수 있는 방법론과 도구를 제안한다. 방법론은 SSD를 구성하는 플래시 메모리의 결함 종류, 결함들을 효과적으로 모니터링 할 수 있는 SMART 속성과 임계값, 그리고 이를 기반으로 SSD의 신뢰성을 예측할 수 있는 모델로 구성된다. 이 방법론은 신뢰성 분석 도구로 구현 되었으며, 이 도구는 Workload generator, SMART monitor, Dependability analyzer, 그리고 GUI viewer로 구성된다. 실제 두 회사에서 생산한 6개의 SSD를 이용하여 실험한 결과, SMART를 기반으로 SSD의 고장 예측이 가능하며, 여러 속성들을 동시에 고려하였을 때 예측의 정확도가 높아짐을 발견하였다.

• Smart Media Journal
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• v.4 no.2
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• pp.62-67
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• 2015

During several decades, hard disk drive(HDD) has been used in most computer systems as secondary storage and, however, the performance enhancement of HDD is limited by its mechanical properties. On the other hand, although the flash memory based solid state drive (SSD) has more advantages over HDD such as high performance and low noise, SSD is still too expensive for common usage and expected to take several years to replace HDD completely. Therefore, SSD caching mechanism using the SSD as a cache of high capacity HDD has been highlighted lately. The representatives of SSD caching mechanisms are typically bcache, dm-cache, Flashcache, and EnhanceIO. Each of them has its own internal mechanism and implementation, and this makes them to show their own pros. and cons. In this paper, we analyze the characteristics of each SSD caching mechanisms and compare the performance of them under various workloads. We expect that our contribution will be useful to enhance the performance of SSD caching mechanisms.

• The Magazine of the IEIE
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• v.41 no.5
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• pp.68-76
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• 2014

• Journal of Digital Convergence
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• v.20 no.5
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• pp.593-598
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• 2022

Recently, data production has seen explosive growth, and the storage systems to store these big data safely and quickly is evolving in various ways. A typical configuration of storage systems is the use of SSDs with fast data processing speed as a RAID group that can maintain reliable data. However, since NAND flash memory, which composes SSD, has the feature that deterioration if writes more than a certain number of times are repeated, can increase the likelihood of simultaneous failure on multiple SSDs in a RAID group. And this can result in serious reliability problems that data cannot be recovered. Thus, in order to solve this problem, we propose a method of throttling IOs so that each SSD within a RAID group leads to a different life-end. The technique proposed in this paper utilizes SMART to control the state of each SSD and the number of IOs allocated according to the data pattern used step by step. In addition, this method has the advantage of preventing large amounts of concurrency defects in RAID because it induces differential lifetime finishes of SSDs.

• Smart Media Journal
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• v.9 no.2
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• pp.92-98
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• 2020

This paper proposes a vehicle license plate recognition system using light weight deep learning models without high-end server. The proposed license plate recognition system consists of 3 steps: [license plate detection]-[character area segmentation]-[character recognition]. SSD-Mobilenet was used for license plate detection, ResNet with localization was used for character area segmentation, ResNet was used for character recognition. Experiemnts using Samsung Galaxy S7 and LG Q9, accuracy showed 85.3% accuracy and around 1.1 second running time.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.142-150
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• 2021

Open-channel SSD is a new type of Solid-State Disk (SSD) that improves the garbage collection overhead and write amplification due to physical constraints of NAND flash memory by exposing the internal structure of the SSD to the host. However, the host-level Flash Translation Layer (FTL) provided for open-channel SSDs in the current Linux kernel consumes host memory excessively because it use page-level mapping table to translate logical address to physical address. Therefore, in this paper, we implemente a selective mapping table loading scheme that loads only a currently required part of the mapping table to the mapping table cache from SSD instead of entire mapping table. In addition, to increase the hit ratio of the mapping table cache, filesystem information and mapping table access history are utilized for cache replacement policy. The proposed scheme is implemented in the host-level FTL of the Linux kernel and evaluated using open-channel SSD emulator. According to the evaluation results, we can achieve 80% of I/O performance using the only 32% of memory usage compared to the previous host-level FTL.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.19-27
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• 2015

Due to the advantages of fast read/write operation and low power consumption, SSD(Solid State Drive) is now widely adopted as storage device of smart phone, laptop computer, server, etc. However, the shortcomings of SSD such as limited number of write operations and asymmetric read/write operation lead to the problem of shortened life span of SSD. Therefore, the block replacement policy of SSD used as cache for HDD is very important. The existing solutions for improving the lifespan of SSD including the LARC scheme typically employ the LRU algorithm to manage the SSD blocks, which may increase the miss rate in SSD due to the replacement of frequently used block instead of rarely used block. In this paper we propose a novel block replacement scheme which considers the block reuse interval to effectively handle various data read/write patterns. The proposed scheme replaces the block in SSD based on the recency decided by reuse interval and age along with hit ratio. Computer simulation using workload trace files reveals that the proposed scheme consistently improves the performance and lifespan of SSD by increasing the hit ratio and decreasing the number of write operations compared to the existing schemes including LARC.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.143-151
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• 2013

NAND flash-based SSDs (Solid State Drive) have advantages of fast input/output performance and low power consumption so that they could be widely used as storages on tablet, desktop PC, smart-phone, and server. But, SSD has the disadvantage of wear-leveling due to increase of the number of writes. In order to improve the lifespan of the SSD, a variety of data deduplication techniques have been introduced. General fixed-size splitting method allocates fixed size of chunk without considering locality of data so that it may execute unnecessary chunking and hash key generation, and variable-size splitting method occurs excessive operation since it compares data byte-by-byte for deduplication. This paper proposes adaptive chunking method based on application locality and file name locality of written data in SSD-based server storage. The proposed method split data into 4KB or 64KB chunks adaptively according to application locality and file name locality of duplicated data so that it can reduce the overhead of chunking and hash key generation and prevent duplicated data writing. The experimental results show that the proposed method can enhance write performance, reduce power consumption and operation time compared to existing variable-size splitting method and fixed size splitting method using 4KB.

• Journal of KIISE
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• v.43 no.7
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• pp.725-735
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• 2016

Smart TV uses Webkit as a web browser engine to provide contents such as web surfing, VOD watching, and games. Webkit uses web resources, such as HTML, CSS, JavaScript, and images, in order to run applications. At the start of an application, Webkit loads resources to the memory and creates DOM tree and render tree, which is a time consuming process. However, DOM tree and render tree created by the smart TV application do not change over time because the smart TV application uses web resources stored in a disk. If DOM tree and render tree can be stored and reused, it is possible to reduce loading time of an application. In this paper, we propose FastIO technique that selectively adds persistency to dynamically allocated memory. FastIO reduces overall application loading time by eliminating the process of loading resources from storage, parsing the HTML documents, and creating DOM tree and render tree. Comparison of the application resource loading times indicates that the web browser with FastIO is 7.9x, 44.8x, and 2.9x faster than the legacy web browser in an SSD, Ramdisk, and eMMC environment, respectively.

• Smart Structures and Systems
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• v.23 no.4
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.