• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.109-110
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• 2019

최근 IoT 환경에서는 고밀도로 노드가 분포되어진다. 이러한 센서 노드들은 데이터 전송 시 혼잡을 초래하는 중복 데이터를 생성하여 데이터의 정확도를 저하시킨다. 이에 따라 본 연구에서는 데이터 집중으로 인해 발생하는 네트워크의 정체 문제를 해결하기 위해 제안 기법은 사 분위(Interquatile, IRQ) 분석과 코사인 유사도 함수를 통해 데이터의 이상치와 중복성을 측정하여 중복 데이터 및 특이치를 제거한다. 본 연구를 통하여 최적의 데이터 전송을 통하여 IoT의 통신 성능을 향상시킬 수 있으며 결과적으로 데이터 감소율, 네트워크 수명 및 에너지의 효율성을 높일 수 있다.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.149-155
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• 2012

SSD is a storage device of having high-performance controller and cache buffer and consists of many NAND flash memories. Because NAND flash memory does not support in-place update, valid pages are invalidated when update and erase operations are issued in file system and then invalid pages are completely deleted via garbage collection. However, garbage collection performs many erase operations of long latency and then it reduces I/O performance and increases wear leveling in SSD. In this paper, we propose a new method of de-duplicating valid data and recycling invalid data. The method de-duplicates valid data and then recycles invalid data so that it improves de-duplication ratio. Due to reducing number of writes and garbage collection, the method could increase I/O performance and decrease wear leveling in SSD. Experimental result shows that it can reduce maximum 20% number of garbage collections and 9% I/O latency than those of general case.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.322-325
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• 2017

Due to the rapid increase in data, various studies are being conducted to efficiently manage the data. In 2025, the total amount of data will increase to more than 163 ZB, and more than a quarter of the data will be a real-time data. As mass storage devices is changed from HDD to SSD, SSD needs own way to manage their data effectively. In this paper, we study the SSD system structure and deduplication management methods of data management related to Flash-SSD. We also propose an application level user file system using deduplication. It is anticipated that it saves storage capacity and minimize reducing performance by unnecessary traffic.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1138-1151
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• 2011

Sensor network clustering scheme is an efficient method that prolongs network lifetime. However, when it is applied to an environment in which collected data of the sensor nodes easily overlap, sensor node unnecessarily consumes energy. Accordingly, we proposed a data prediction scheme that sensor node can predict current data to exclude redundant data transmission and to minimize data transmission among the cluster head node and member nodes. Our scheme excludes redundant data collection by neighbor nodes. Thus it is possible that energy efficient data transmission. Moreover, to alleviate unnecessary data transmission, we introduce data prediction graph whether transmit or not through analyze between prediction and current data. According to the result of performance analysis, our method consume less energy than the existing clustering method. Nevertheless, transmission efficiency and data accuracy is increased. Consequently, network lifetime is prolonged.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.150-154
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• 2008

무한 웹 컨텐츠 환경에서는 사용자의 컨텐츠 선택을 용이하게 하기 위하여 메타데이터를 다양한 방법으로 수집할 수 있다. 그러나 한 가지 방법으로는 메타데이터의 수신이 제한적이고 풍부한 메타데이터 수신을 위해서는 다양한 방법을 이용해야 한다. 그래서 본 논문에서는 메타데이터 수집 방법들을 통합하는 장치를 제안하고, 통합 메타데이터의 품질 향상을 위해 통합과정에서 발생하는 중복 메타데이터의 필터링 방법을 제시 및 검증한다. 구체적으로는 현재 웹 상에서 다양하게 제공되고 있는 메타데이터 수집 기능들을 분석하고, 통합 장치의 개념적인 구조를 제시하며, 웹 상에서 많이 보급되고 있는 RSS Reader를 통해 메타데이터를 수집하고 이를 토대로 분석하여 중복 컨텐츠를 판단하는 방법을 제안하였다.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.1-8
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• 2020

The need for storage, management, and retrieval techniques for alternative data has emerged as technologies based on data generated from business activities conducted by enterprises have emerged as the key to business success in recent years. Existing big data platform systems must load a large amount of data generated in real time without delay to process unstructured data, which is an alternative data, and efficiently manage storage space by utilizing a deduplication system of different storages when redundant data occurs. In this paper, we propose a multi-layer distributed data deduplication process system using the similarity of the Cuckoo hashing filter technique considering the characteristics of big data. Similarity between virtual machines is applied as Cuckoo hash, individual storage nodes can improve performance with deduplication efficiency, and multi-layer Cuckoo filter is applied to reduce processing time. Experimental results show that the proposed method shortens the processing time by 8.9% and increases the deduplication rate by 10.3%.

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.623-631
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• 2014

Comparison of two representative deduplication file systems, LessFS and SDFS, shows that Lessfs is better in execution time and CPU utilization while SDFS is better in storage usage (around 1/8 less than general file systems). In this paper, a new system is proposed where the advantages of SDFS and Lessfs are combined. The new system uses multiple DFEs and one DSE to maintain the integrity and consistency of the data. An evaluation study to compare between Single DFE and Dual DFE indicates that the Dual DFE was better than the Single DFE. The Dual DFE reduced the CPU usage and provided fast deduplication time. This reveals that proposed system can be used to solve the problem of an increase in large data storage and power consumption.

• KIISE Transactions on Computing Practices
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• v.22 no.8
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• pp.369-374
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• 2016

The growing demand of virtual computing and storage resources in the cloud computing environment has led to deduplication of storage system for effective reduction and utilization of storage space. In particular, large reduction in the storage space is made possible by preventing data with identical content as the virtual desktop images from being stored on the virtual desktop infrastructure. However, in order to provide reliable support of virtual desktop services, the storage system must address a variety of workloads by virtual desktop, such as performance overhead due to deduplication, periodic data I/O storms and frequent random I/O operations. In this paper, we designed and implemented a clustered file system to support virtual desktop and storage services in cloud computing environment. The proposed clustered file system provides low storage consumption by means of inline deduplication on virtual desktop images. In addition, it reduces performance overhead by deduplication process in the data server and not the virtual host on which virtual desktops are running.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.83-94
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• 2015

Deduplication, which is a technique of eliminating redundant data by storing only a single copy of each data, provides clients and a cloud server with efficiency for managing stored data. Since the data is saved in untrusted public cloud server, however, both invasion of data privacy and data loss can be occurred. Over recent years, although many studies have been proposed secure deduplication schemes, there still remains both the security problems causing serious damages and inefficiency. In this paper, we propose secure and efficient client-side deduplication with Key-server based on Bellare et. al's scheme and challenge-response method. Furthermore, we point out potential risks of client-side deduplication and show that our scheme is secure against various attacks and provides high efficiency for uploading big size of data.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.9
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• pp.321-326
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• 2015

In this paper, we proposed an algorithm which could transmit reliable data between smart devices by using inaudible high frequency of audible frequency range and cyclic redundancy check method. The proposed method uses 18 kHz~22 kHz as high frequency which inner speaker of smart device can make a sound in audible frequency range (20 Hz~22 kHz). To increase transmission quantity of data, we send mixed various frequencies at high frequency range 1 (18.0 kHz~21.2 kHz). At the same time, to increase accuracy of transmission data, we send some mixed frequencies at high frequency range 2 (21.2 kHz~22.0 kHz) as checksum. We did experiments about data transmission between smart devices by using the proposed method to confirm data transmission speed and accuracy of the proposed method. From the experiments, we showed that the proposed method could transmit 32 bits data in 235 ms, the transmission success rate was 99.47%, and error detection by using cyclic redundancy check was 0.53%. Therefore, the proposed method will be a useful for wireless transmission technology between smart devices.