• KIPS Transactions on Computer and Communication Systems
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• v.4 no.9
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• pp.307-314
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• 2015

Recently, market trends of auxiliary storage device HDD and SSD are interchangeable. In the future, the SSD is expected to be used more popular than HDD as an auxiliary storage device. The TRIM command technique has been proposed and used effectively due to the development of the SSD. The TRIM command techniques can be used to solve the problem of Freezing SSD that operating system cooperates with the SSD. The TRIM command techniques are performed in the idle time of the internal SSD that are actually deleted when a user deletes the data. However, in the point of view of computer forensics, the digital crime is increasing year by year due to lack of data recovery. Thus, this rate of arrest is insufficient. In this paper, I propose a solution that selectively manages data to delete based on advantage of the stability and the write speed of the TRIM command. Through experiments, It is verified by measuring the performance of the traditional method and selected method.

• Journal of KIISE
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• v.42 no.6
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• pp.691-698
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• 2015

Application launch time is an important performance metric to user experience in desktop and laptop environment, which mostly depends on the performance of secondary storage. Application launch times can be reduced by utilizing solid-state drive (SSD) instead of hard disk drive (HDD). However, considering a cost-performance trade-off, utilizing SSDs as caches for slow HDDs is a practicable alternative in reducing the application launch times. We propose a new SSD caching scheme which migrates data blocks from HDDs to SSDs. Our scheme operates entirely in the file system level and does not require an extra layer for mapping SSD-cached data that is essential in most other schemes. In particular, our scheme does not incur mapping overheads that cause significant burdens on the main memory, CPU, and SSD space for mapping table. Experimental results conducted with 8 popular applications demonstrate our scheme yields 56% of performance gain in application launch, when data blocks along with metadata are migrated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.11-15
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• 2015

SSD(Solide State Disk) Memory is gradually replacing HDD(Hard Disk Drive) for high speed data input and output processing on Internet server system. In this paper, we proposed efficient data distribution storage algorithm in DRAM based SSD. And we did performance test for proposed algorithm and existing algorithm in the same server environment condition. The result of comparison of performance test is as fellows. Data backup processing time of proposed algorithm was reduced by half than that of existing algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.45-52
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• 2020

This paper proposes a solution for storage and retrieval problems for Resource Description Framework (RDF) data utilizing a key-value Solid State Device (SSD), considering storage, retrieval performance, and security. We propose a two-step compression algorithm to separate logical relationship and true values from RDF data-sets using the key-value SSD. This improves not only compression and storage efficiency but also storage security. We also propose a hybrid retrieval structure based on R∗-tree to enhance retrieval efficiency and implement a sort-merge join algorithm, and discuss factors affecting R∗-tree retrieval efficiency. Finally, we show the proposed approach is superior to current compression, storage, and retrieval approaches, obtaining target results faster while requiring less space, and competitive in terms of versatility, flexibility and security.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1031-1040
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• 2010

Hash join is one of the core algorithms in databases management systems. If a hash join cannot complete in one-pass because the available memory is insufficient (i.e., hash table overflow), however, it may incur a few sequential writes and excessive random reads. With harddisk as the tempoary storage for hash joins, the I/O time would be dominated by slow random reads in its probing phase. Meanwhile, flash memory based SSDs (flash SSDs) are becoming popular, and we will witness in the foreseeable future that flash SSDs replace harddisks in enterprise databases. In contrast to harddisk, flash SSD without any mechanical component has fast latency in random reads, and thus it can boost hash join performance. In this paper, we investigate several important and practical issues when flash SSD is used as tempoary storage for hash join. First, we reveal the va patterns of hash join in detail and explain why flash SSD can outperform harddisk by more than an order of magnitude. Second, we present and analyze the impact of cluster size (i.e., va unit in hash join) on performance. Finally, we emperically demonstrate that, while a commerical query optimizer is error-prone in predicting the execution time with harddisk as temporary storage, it can precisely estimate the execution time with flash SSD. In summary, we show that, when used as temporary storage for hash join, flash SSD will provide more reliable cost estimation as well as fast performance.

• International Journal of Contents
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• v.5 no.4
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• pp.75-80
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• 2009

Recently high-speed memory array based on RAM, which is a type of solid-state drive (SSD), has been introduced to handle the input/output (I/O) bottleneck. But there are only a few performance studies on RAM based SSD storage with regard to diverse workloads. In this paper, we focus on the file system for RAM based memory array based NGS (Next Generation Storage) system which is running on Linux operating system. Then we perform benchmark tests on practical file systems including Ext3, ReiserFS, XFS. The result shows XFS significantly outperforms other file systems in tests that represent the storage and data requests typically made by enterprise applications in many aspects. The experiment is used to design the dedicated file system for NGS system. The results presented here can help enterprises improve their performance significantly.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.237-238
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• 2014

최근 낸드 플래시 기반의 SSD가 상용화 되면서 기존의 HDD 저장 장치와 SSD를 함께 사용하는 Hybrid 저장장치에 대한 연구가 되고 있다. SSD의 빠른 읽기 및 쓰기 속도와 HDD의 대용량을 함께 효율적으로 사용하기 위하여 본 논문에서는 메모리에서 방출된 페이지들을 구별하여 각각의 저장장치에 저장하는 모델을 제안하였다. 이를 통하여 Hybrid 저장장치에서 SSD의 GC(Garbage Collection)을 최대한 줄임으로써 쓰기 속도를 향상시키고 HDD의 대용량 저장장치를 이용하여 전체적인 성능이 향상 된 것을 증명하였다.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.218-219
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• 2008

Solid State Disks(SSD) are one of the best candidates to support next storage technology in desktop and server computing environment. The features of non-volatility, low power consumption, and fast access time for read operations are sufficient grounds to support SSD as major components of future storages. This paper describes a technical trend of HDD based RAID technology and proposes a new RAID system for SSD.

• 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

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.460-470
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• 2017

We address how to handle big data mining effectively using the intelligent SSD (iSSD). ISSD is a storage device equipped with computing power inside SSD for reducing the transferring cost and for processing data nearby SSD where the data is stored. We first introduce the structural characteristics of iSSD for efficient data processing. Then, we present how to process data mining algorithms by using iSSD. Finally, we discuss how to improve the performance of data mining algorithms significantly by exploiting heterogeneous computing environment where host CPUs and GPU coexist for maximizing the performance.