• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.963-967
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• 2009

The Log-structured File System (LFS) collects all modified data into a memory buffer and writes them sequentially to a segment on disk. Therefore, it has the potential to utilize the maximum bandwidth of storage devices where sequential writes are much faster than random writes. However, as disk space is finite, LFS has to conduct cleaning to produce free segments. This cleaning operation is the main reason LFS performance deteriorates when file system utilization is high. To overcome painful cleaning and reduced performance of LFS, we propose the segment space recycling (SSR) scheme that directly writes modified data to invalid areas of the segments and describe the classification method of data and segment to consider locality of reference for optimizing SSR scheme. We implement U-LFS, which employs our segment space recycling scheme in LFS, and experimental results show that SSR scheme increases performance of WOLF by up to 1.9 times in HDD and 1.6 times in SSD when file system utilization is high.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.92-99
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• 2005

In this paper, we present a high-level design methodology applied on a network system-on-a-chip(SOC) using SystemC. The main target of our approach is to get optimum performance parameters for high network address translation(NAT) throughput. The Fast Ethernet media access controller(MAC) and its direct memory access(DMA) controller are modeled with SystemC in transaction level. They are calibrated through the cycle-based measurement of the operation of the real Verilog register transfer language(RTL). The NAT throughput of the model is within $\pm$10% error compared to the output of the real evaluation board. Simulation speed of the model is more than 100 times laster than the RTL. The validated models are used for intensive architecture exploration to find the performance bottleneck in the NAT router.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.15-23
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• 2018

A code reuse attack is an attack technique that can execute arbitrary code without injecting code directly into the stack by combining executable code fragments existing in program memory and executing them continuously. ROP(Return-Oriented Programming) attack is typical type of code reuse attack and serveral defense techniques have been proposed to deal with this. However, since existing methods use Rule-based method to detect attacks based on specific rules, there is a limitation that ROP attacks that do not correspond to previously defined rules can not be detected. In this paper, we introduce a method to detect ROP attack by learning command pattern used in ROP attack code using RNN(Recurrent Neural Network). We also show that the proposed method effectively detects ROP attacks by measuring False Positive Ratio, False Negative Ratio, and Accuracy for normal code and ROP attack code discrimination.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.52-57
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• 2015

In this paper, we analyze the performance of the TRIM commands on various SSDs and, based on our analysis results, we enhance the performance of these TRIM commands in the Ext4 file system. We observed that the performance of the TRIM commands improves as the size of the LBA-range increases, the sector number is aligned and continuous or more LBA-ranges are notified via a single TRIM command. However, although the performance is better when multiple LBA-ranges are informed by a single TRIM command, the Ext4 file system issues a single TRIM command for every LBA-range. In this paper, we modify the Ext4 file system to convey at most 64 LBA-ranges per TRIM command. Evaluations through Filebench show that the performance of file deletion operations is improved by up to 35%.

• Journal of KIISE
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• v.42 no.12
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• pp.1474-1479
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• 2015

With mobile devices showing marked improvement in performance in the age of the Internet of Things (IoT), there is demand for rapid processing of the extensive amount of multimedia big data. However, because research on image searching is focused mainly on increasing accuracy despite environmental changes, the development of fast processing of high-resolution multimedia data queries is slow and inefficient. Hence, we suggest a new distributed image search algorithm that ensures both high accuracy and rapid response by using feature extraction of distributed images based on MapReduce, and solves the problem of memory scalability based on BIRCH indexing. In addition, we conducted an experiment on the accuracy, processing time, and scalability of this algorithm to confirm its excellent performance.

• Convergence Security Journal
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• v.13 no.4
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• pp.101-108
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• 2013

Sensor network configurations are for a specific situation or environment sensors capable of sensing, processing the collected information processors, and as a device is transmitting or receiving data. It is presently serious that sensor networks provide many benefits, but can not solve the wireless network security vulnerabilities, the risk of exposure to a variety of state information. u-Healthcare sensor networks, the smaller the sensor node power consumption, and computing power, memory, etc. restrictions imposing, wireless sensing through the kind of features that deliver value, so it ispossible that eavesdropping, denial of service, attack, routing path. In this paper, with a focus on sensing of the environment u-Healthcare system wireless security vulnerabilities factors u-Healthcare security framework to diagnose and design methods are presented. Sensor network technologies take measures for security vulnerabilities, but without the development of technology, if technology is not being utilized properly it will be an element of threat. Studies suggest that the u-Healthcare System in a variety of security risks measures user protection in the field of health information will be used as an important guide.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10A
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• pp.823-829
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• 2011

Recently, wireless body area network (WBAN) has received much attention as an application for the ubiquitous healthcare system. In WBAN, each sensor nodes and a personal base station such as PDA have an energy constraint and computation overhead should be minimized due to node's limited computing power and memory constraint. The reliable data transmission also must be guaranteed because it handles vital signals. In this paper, we propose a systematic network coding scheme for WBAN to reduce the network coding overhead as well as total energy consumption for completion the transmission. We model the proposed scheme using Markov chain. To minimize the total energy consumption for completing the data transmission, we made the problem as a minimization problem and find an optimal solution. Our simulation result shows that large amount of energy reduction is achieved by proposed systematic network coding. Also, the proposed scheme reduces the computational overhead of network coding imposed on each node by simplify the decoding process.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.435-447
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• 2004

For VOD systems, it is important to provide QoS to more users under the limited resources. To analyze QoS issues in real environment, we implement clustered VOD server and embedded client system based on the Linux open source platform. The parallel processing of MPEG data, load balancing for nodes and VCR like functions are implemented in the server side. To provide more user friendly interface, the general TV is used for a VOD client's terminal and the embedded board is used supporting for VCR functions. In this paper, we measure the performance of the implemented VOD system under the various user requirement features and evaluate the sources of performance limitations. From these analyses, we propose the dynamic admission control method based on the availability memory and network bandwidth. The proposed method enhances the utilization of the system resource for the more QoS media streams.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.201-208
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• 2016

Collection and storing of multiple time series data in real time requires large memory space. To solve this problem, the usage of varying sample size is proposed in the compression scheme using discrete cosine transform technique. Time series data set has characteristics such that a higher compression ratio can be achieved with smaller amount of value changes and lower frequency of the value changes. The coefficient of variation and the variability of the differences between adjacent data elements (VDAD) are presumed to be very good measures to represent the characteristics of the time series data and used as key parameters to determine the varying sample size. Test results showed that both VDAD-based and the coefficient of variation-based scheme generate excellent compression ratios. However, the former scheme uses much simpler sample size decision mechanism and results in better compression performance than the latter scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.509-516
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• 2008

Recently, the operator modules to control external devices are concerned about automatic management system to process continuously changed signals. These signals are the stream data of which characteristics are several numbers. a short report interval and asynchronous report time. It is necessary that the system brings about high accuracy and real time process for stream data. The typical queries of these systems consist of the current query to search the latest signal value, the snapshot query at a past time, the sliding window query from a past time to current. In this paper, we propose the efficient method to manage the above signals by using a file structured database in small-size operating systems. We also propose a query model to accommodate various queries including the sliding window query. The file database in the QNX adopts a delta version and a shared memory buffering method for the resource limit of a small storage and a low computing power.