• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1999-2007
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• 2010

Proxy Mobile IPv6(PMIPv6) is a network-based mobility management protocol and it does not require mobile node's involving in mobility management. In PMIPv6, the Mobile Access Gateway (MAG) incurs a high signaling cost to update the location of a mobile node to the remote Local Mobility Anchor (LMA) if it moves frequently. It may cause excessive signaling traffic and increase a high traffic load on LMA. Therefore, we propose a new mobility management scheme in proxy mobile IPv6 networks with dynamic paging support. To minimize signaling overhead, in our proposal, the size of the paging area is determined dynamically according the changes of mobility and traffic patterns of the mobile node. An analytic model is applied to determine the optimal size of the paging area. The cost analysis using fluid flow model presented in this paper shows that our proposal can achieve performance superior that of PMIPv6 scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2167-2175
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• 2017

In recent years, an IoT is dramatically developing according to the enhancement of AI, the increase of connected devices, and the high-performance cloud systems. Huge data produced by many devices and sensors is expanding the scope of services, such as an intelligent diagnostics, a recommendation service, as well as a smart monitoring service. The studies of edge computing are limited as a role of small server system with high quality HW resources. However, there are specialized requirements in a smart factory domain needed edge computing. The edges are needed to pre-process containing tiny filtering, pre-formatting, as well as merging of group contexts and manage the regional rules. So, in this paper, we extract the features and requirements in a scope of efficiency and robustness. Our edge offers to decrease a network resource consumption and update rules and learning models. Moreover, we propose architecture of edge computing based on learning factors sharing with a cloud system in a smart factory.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.814-821
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• 2012

We propose a network processor called an OmniFlow processor capable of wire-speed flow management by a hardware-based flow admission control(FAC) in this paper. Because the OmniFlow processor can set up and release a wire-speed connection for flows, the update period of flows can be set to a short time, and only active flows can be effectively managed by terminating a flow that does not have a packet transmitted within this period. Therefore, the FAC can be used to provide a reliable transmission of UDP as well as TCP applications. This processor is fabricated in 65nm CMOS technology, and total gate count is 25 million. It has 40 Gb/s throughput performance in using the 32 RISC cores when maximum operating frequency is 555MHz.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.322-330
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• 2009

In order to utilize NAND flash memory as storage media which does not allow update-in-place and limits the number of block erase count, various garbage collection policies supporting wear-leveling have been investigated. Conventional garbage collection policies require cleaning-index calculation for the entire blocks to choose a block to be garbage-collected to support wear-leveling whenever a garbage collection is required, which results in performance degradation of system. This paper proposes a garbage collection policy which supports wear-leveling using a threshold value, which is in fact a variance of erase counts and by the maximum erase count of all blocks, without calculating the cleaning-index. During garbage collection, the erase cost is minimized by using the Greedy Policy if the variance is less than the threshold value. It achieves wear-leveling by excluding the block with the largest erase count from erase target blocks if the variance is larger than threshold value. The proposed scheme shows that a standard deviation approaches to zero as the erase count of blocks approaches to its upper limit and the measured speed of garbage collection is two times faster than the conventional schemes.

• Journal of KIISE:Information Networking
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• v.34 no.6
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• pp.458-465
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• 2007

Wireless Sensor Network(WSN) is a special network that collects measured data by sensor nodes in the predefined sensor field and forwards them to the base station in a distance using their own routing scheme. WSN requires routing techniques to maximize energy efficiency because sensor nodes have non-rechargeable and thus limited energy. Characteristics of WSN are various according to applications, many of routing algorithms have been proposed. This paper proposes an algorithm called A-PEGASIS that basically bases on PEGASIS and enhances in two aspects - an elegant chain generation algorithm and periodical update of chains. We compare performance of the previous algorithm of LEACH, PEGASIS, PEDAP and PEDAP-PA with ours through simulation. It confirms that the A-PEGASIS is most superior in terms of average WSN lifetime and high probability of node survival rate during WSN life time.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.9
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• pp.445-456
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• 2017

In this paper, we propose a method to detect spam tweets containing unhealthy information by using an n-gram dictionary under limited labeling. Spam tweets that contain unhealthy information have a tendency to use similar words and sentences. Based on this characteristic, we show that spam tweets can be effectively detected by applying a Naive Bayesian classifier using n-gram dictionaries which are constructed from spam tweets and normal tweets. On the other hand, constructing an initial training set requires very high cost because a large amount of data flows in real time in a twitter. Therefore, there is a need for a spam detection method that can be applied in an environment where the initial training set is very small or non exist. To solve the problem, we propose a method to generate pseudo-labels by utilizing twitter's retweet function and use them for the configuration of the initial training set and the n-gram dictionary update. The results from various experiments using 1.3 million korean tweets collected from December 1, 2016 to December 7, 2016 prove that the proposed method has superior performance than the compared spam detection methods.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.236-242
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• 2010

A GNSS/INS integration system can not provide navigation solutions if there are no available satellites. To overcome this problem, a vision sensor is integrated with this system. Since generally a vision aided integration system uses only feature point to compute navigation solutions, it has a problem in observability. In this case, additional landmarks, which is priory known points, can improve the observability. In this paper, the observability is evaluated using TOM/SOM matrix and Eigenvalues. There are always the observability problems in the feature-point-only case, but the landmark-use case is fully observable after the $2^{nd}$ update time. Consequently the landmarks ensure full observability, so the system performance can be improved.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.167-179
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• 2017

In this paper, a simplified Cubature Kalman Filter (SCKF) is proposed to reduce the computation load of CKF, which is then used as a filter for transfer alignment of shipboard INS. CKF is an approximate Bayesian filter that can be applied to non-linear systems. When an initial estimation error is large, convergence characteristic of the CKF is more stable than that of the Extended Kalman Filter (EKF), and the reliability of the filter operation is more ensured than that of the Unscented Kalman Filter (UKF). However, when a system degree is large, the computation amount of CKF is also increased significantly, becoming a burden on real-time implementation in embedded systems. A simplified CKF is proposed to address this problem. This filter is applied to shipboard inertial navigation system (INS) transfer alignment. In the filter design for transfer alignment, measurement type and measurement update rate should be determined first, and if an application target is a ship, lever-arm problem, flexure of the hull, and asynchronous time problem between Master Inertial Navigation System (MINS) and Slave Inertial Navigation System (SINS) should be taken into consideration. In this paper, a transfer alignment filter based on SCKF is designed by considering these problems, and its performance is validated based on simulations.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.2
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• pp.103-113
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• 2001

This paper described a design and implementation of a single-chip encoder/decoder using the LZSS algorithm and entropy coding in 0.6${\mu}{\textrm}{m}$ CMOS technology. Dictionary storage for the dictionary search processor(DISP) used a 2K$\times$8bit on-chip memory with 50MHz clock speed. It performs compression on byte-oriented input data at a data rate of one byte per clock cycle except when one out of every 33 cycles is used to update the string window of dictionary. In result, the average compression ratio is 46% by applied entropy coding of the LZSS codeword output. This is to improved on the compression performance of 7% much more then LZSS.

• The Journal of the Acoustical Society of Korea
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• v.11 no.1
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• pp.22-34
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• 1992

There exists a transform trellis code that is optimal for stationary Gaussian sources and the squared-error distortion measure at all rates. In this paper, we train an asymptotically optimal version of such a code to obtain one which is matched better to the statistics of real world data. The training algorithm uses the M algorithm to search the trellis codebook and the LBG algorithm to update the trellis codebook. We investigate the trained transform trellis coding scheme for the first-order AR(autoregressive) Gaussian source whose correlation coefficient is 0.9 and actual speech sentences. For the first-order AR source, the achieved SNR for the test sequence is from 0.6 to 1.4 dB less than the maximum achievable SNR as given by Shannon's rate-distortion function for this source, depending on the rate and surpasses all previous known results for this source. For actual speech data, to achieve improved performance, we use window functions and gain adaptation at rate 1.0 bits/sample.