• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.813-818
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• 2020

Recently, with the rapid increase in technology and users of smart devices, the smart watch market has grown, and its utility and usability are continuously expanding. The strengths of smartwatches are wearable portability, application immediacy, data diversity and real-time capability. Despite these strengths, smartwatches have limitations such as battery limitations, display and user interface size limitations, and memory limitations. In addition, there is a need to supplement developers and standard devices, operating system standard models, and killer application modules. In particular, monitoring and application of user's biometric information is becoming a major service for smart watches. The biometric information of such a smart watch generates a large amount of data in real time. In order to advance the biometric information service, stable peer-to-peer transmission of sensing data to a remote smartphone or local server storage must be performed. We propose a synchronization method to ensure wireless remote peer-to-peer transmission stability in a smart watch system. We design a wireless peer-to-peer transmission process based on this synchronization method, analyze asynchronous transmission process and proposed synchronous transmission process, and propose a transmission efficiency method according to an increase in transmission amount.

• Journal of the Korea Computer Graphics Society
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• v.17 no.3
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• pp.1-7
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• 2011

Recently, various researches have been proposed to accelerate GPU-based volume ray-casting. However, those researches may cause several problems such as bottleneck of data transmission between CPU and GPU, requirement of additional video memory for hierarchical structure and increase of processing time whenever opacity transfer function changes. In this paper, we propose an efficient GPU-based empty space skipping technique to solve these problems. We store maximum density in a brick of volume dataset on a vertex element. Then we delete vertices regarded as transparent one by opacity transfer function in geometry shader. Remaining vertices are used to generate bounding boxes of non-transparent area that helps the ray to traverse efficiently. Although these vertices are independent on viewing condition they need to be reproduced when opacity transfer function changes. Our technique provides fast generation of opaque vertices for interactive processing since the generation stage of the opaque vertices is running in GPU pipeline. The rendering results of our algorithm are identical to the that of general GPU ray-casting, but the performance can be up to more than 10 times faster.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2B
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• pp.100-107
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• 2007

Recently, a study of BcN(Broadband convergence Network) is progressing continuously, and it is important to improve the quality of the service according to subscribers because a scale of network is about to be larger. It is more important to manage QoS(Quality of Service) of all subscribers in layer 2 than layer 3 network since managing it in layer 3 network cost both additional processes and large hardware. Moreover, QoS based on Best-Effort service has been developed because tots of subscribers should use limited resource in BcN. However, they want to be supplied with different service even though they pay more charge. Therefore, it is essential to assign the different bandwidth to subscribers depending on their level of charge. The method of current Rate Limiter limits the bandwidth of each port that does not offer fair service to subscribers. The Rate Limiter proposed in this paper limits bandwidth according to each subscriber. Therefore, subscribers can get fair service regardless of switch structure. This new Rate Limiter controls the bandwidth of subscribers according to the information of learning subscriber and manages maximum performance of Ethernet switch and QoS.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.7
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• pp.761-768
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• 2010

This paper presents an effective method to achieve the wideband waveform for high resolution SAR(Synthetic Aperture Radar) using the frequency multiplication technique. And also this paper analyzes the root causes for the spectral regrowth due to 3rd-order intermodulation in chirp bandwidth expansion scheme using quadrature modulator and frequency multipliers. The amplitude and phase imbalance requirement are defined based on the simulation results in terms of quadrature channel imbalance. This minimizes the degradation of range resolution, peak sidelobe ratio and integrated sidelobe ratio. The wideband chirp generator using the frequency multiplier and memory map scheme was manufactured and the compensation technique was presented to reduce the spectral regrowth of SAR waveform by minimizing the amplitude and phase imbalance. After I and Q channel imbalance adjustment, the carrier level reduces －28.7 dBm to －53.4 dBm. Chirp signal with 150 MHz bandwidth at S-band expands to 600 MHz bandwidth at X-band. The sidelobe levels are reduced by about 8 to 9 dB by compensating the amplitude balance between I and Q channels.

• The KIPS Transactions:PartA
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• v.19A no.3
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• pp.129-138
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• 2012

In distributed memory architectures like clusters, each node stores a portion of data. How data is distributed across nodes influences the performance of such systems. The data distribution scheme is the strategy to distribute data across nodes and realize parallel data processing. Due to various reasons such as maintenance, scale up, upgrade, etc., the performance of nodes in a cluster can often become non-identical. In such clusters, data distribution without considering performance cannot efficiently distribute data on nodes. In this paper, we propose a new data distribution scheme based on the number of cores in nodes. We use the number of cores as the performance factor. In our data distribution scheme, each node is allocated an amount of data proportional to the number of cores in it. We implement our data distribution scheme using the Chapel language. To show our data distribution is effective in reducing the execution time of parallel applications, we implement Mandelbrot Set and ${\pi}$-Calculation programs with our data distribution scheme, and compare the execution times on a cluster. Based on experimental results on clusters of 8-core and 16-core nodes, we demonstrate that data distribution based on the number of cores can contribute to a reduction in the execution times of parallel programs on clusters.

• The KIPS Transactions:PartA
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• v.19A no.3
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• pp.139-146
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• 2012

In the server cluster environment, one of the ways saving energy is to control server's power according to traffic conditions. This is to determine the ON/OFF state of servers according to energy usage of data center and each server. To do this, we need a way to estimate each server's energy. In this paper, we use a software-based power consumption estimation model because it is more efficient than the hardware model using power meter in terms of energy and cost. The traditional software-based power consumption estimation model has a drawback in that it doesn't know well the computing status of servers because it uses only the idle status field of CPU. Therefore it doesn't estimate consumption power effectively. In this paper, we present a CPU field based power consumption estimation model to estimate more accurate than the two traditional models (CPU/Disk/Memory utilization based power consumption estimation model and CPU idle utilization based power consumption estimation model) by using the various status fields of CPU to get the CPU status of servers and the overall status of system. We performed experiments using 2 PCs and compared the power consumption estimated by the power consumption model (software) with that measured by the power meter (hardware). The experimental results show that the traditional model has about 8-15% average error rate but our proposed model has about 2% average error rate.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.2
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• pp.55-61
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• 2017

In radio astronomy, high-capacity HDDs are being used to save huge amounts of HDDs in order to record the observational data. For VLBI observations, observational speeds increase and huge amounts of observational data must be stored as they expand to broadband. As the HDD is frequently used, the number of failures occurred, and then it takes a lot of time to recover it. In addition, if a failed HDD is continuously used, observational data loss occurs. And it costs a lot of money to buy a new HDD. In this study, we developed the integrity verification system of the Serial ATA HDD using FirmOS. The FirmOS is an OS that has been developed to function exclusively for specific purposes on a system having a general server board and CPU. The developed system performs the process of writing and reading specific patterns of data in a physical area of the SATA HDD based on a FirmOS. In addition, we introduced a method to investigate the integrity of HDD integrity by comparing it with the stored pattern data from the HDD controller. Using the developed system, it was easy to determine whether the disk pack used in VLBI observations has error or not, and it is very useful to improve the observation efficiency. This paper introduces the detail for the design, configuration, testing, etc. of the SATA HDD integrity verification system developed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2B
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• pp.36-43
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• 2005

This paper suggests a method to effectively apply an application model of fuzzy-neural network to the optimal load distribution algorithm, considering the complication and non-linearity of the web server environment. We use the clustering web server in the linux system and it consists of a load balancer that distributes the network loads and some of real servers that processes the load and responses to the client. The previous works considered only with the scrappy decision information such as the connections. That is, since the distribution algorithm depends on the input of the whole network throughput, it was proved inefficient in terms of performance improvement of the web server. With the proposed algorithm, it monitors the whole states of both network input and output. Then, it infers CPU and memory states of each real server and effectively distributes the requests of the clients. In this paper, the proposed model is compared with the previous method through simulations and we analysis the results to develop the optimal and intelligent load balancing model.

• Journal of KIISE:Databases
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• v.33 no.6
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• pp.563-577
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• 2006

A stream processor uses resource sharing method for efficient of limited resource in multiple continuous queries. The previous methods process aggregate queries to consist the level structure. So insert operation needs to reconstruct cost of the level structure. Also a search operation needs to search cost of aggregation information in each size of sliding windows. Therefore this paper uses linear structure for optimization of sliding window aggregations. The method comprises of making decision, generation and deletion of panes in sequence. The decision phase determines optimum pane size for holding accurate aggregate information. The generation phase stores aggregate information of data per pane from stream buffer. At the deletion phase, panes are deleted that are no longer used. The proposed method uses resources less than the method where level structures were used as data structures as it uses linear data format. The input cost of aggregate information is saved by calculating only pane size of data though numerous stream data is arrived, and the search cost of aggregate information is also saved by linear searching though those sliding window size is different each other. In experiment, the proposed method has low usage of memory and the speed of query processing is increased.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.113-124
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• 2009

With increasing multicore system, much effort has been put on the performance improvement of its application. Because multicore system has multiple processing devices in one system, its processing power increases compared to the single core system. However in many cases the advantages of multicore can not be exploited fully because the existing software and hardware were designed to be suitable for single core. When the existing software runs on multicore, its performance improvement is limited by the bottleneck of sharing resources and the inefficient use of cache memory on multicore. Therefore, according as the number of core increases, it doesn't show performance improvement and shows performance drop in the worst case. In this paper we propose a method of performance improvement of multicore system by applying Flow-Level Parallelism to the existing TCP/IP network application and operating system. The proposed method sets up the execution environment so that each core unit operates independently as much as possible in network application, TCP/IP stack on operating system, device driver, and network interface. Moreover it distributes network traffics to each core unit through L2 switch. The proposed method allows to minimize the sharing of application data, data structure, socket, device driver, and network interface between each core. Also it allows to minimize the competition among cores to take resources and increase the hit ratio of cache. We implemented the proposed methods with 8 core system and performed experiment. Experimental results show that network access speed and bandwidth increase linearly according to the number of core.