• Journal of KIISE
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• v.41 no.9
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• pp.674-685
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• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.8
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• pp.181-188
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• 2016

Recently, as the amount of spatial information increases, an interest in the study of spatial information processing has been increased. Spatial database systems extended from the traditional relational database systems are difficult to handle large data sets because of the scalability. SpatialHadoop extended from Hadoop system has a low performance, because spatial computations in SpationHadoop require a lot of write operations of intermediate results to the disk, resulting in the performance degradation. In this paper, Spatial Computation Spark(SC-Spark) is proposed, which is an in-memory based distributed processing framework. SC-Spark is extended from Spark in order to efficiently perform the spatial operation for large-scale data. In addition, SC-Spark based on the GPGPU is developed to improve the performance of the SC-Spark. SC-Spark uses the advantage of the Spark holding intermediate results in the memory. And GPGPU-based SC-Spark can perform spatial operations in parallel using a plurality of processing elements of an GPU. To verify the proposed work, experiments on a single AMD system were performed using SC-Spark and GPGPU-based SC-Spark for Point-in-Polygon and spatial join operation. The experimental results showed that the performance of SC-Spark and GPGPU-based SC-Spark were up-to 8 times faster than SpatialHadoop.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2784-2790
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• 2015

The column-oriented database storage is a very advanced model for large-volume data transactions because of its superior I/O performance. Traditional data storages exploit row-oriented storage where the attributes of a record are placed contiguously in hard disk for fast write operations. However, for search-mostly data warehouse systems, column-oriented storage has become a more proper model because of its superior read performance. Recently, solid state drive using flash memory is largely recognized as the preferred storage media for high-speed data analysis systems. In this research, we propose a new transaction recovery scheme for a column-oriented database environment which is based on a flash media file system. We improved traditional shadow paging schemes by reusing old data pages which are supposed to be invalidated in the course of writing a new data page in the flash file system environment. In order to reuse these data pages, we exploit reused shadow list structure in our column-oriented shadow recovery(CoSR) scheme. CoSR scheme minimizes the additional storage overhead for keeping shadow pages and minimizes the I/O performance degradation caused by column data compression of traditional recovery schemes. Based on the results of the performance evaluation, we conclude that CoSR outperforms the traditional schemes by 17%.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.313-322
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• 2005

In this paper, we implement and verify performance monitor for parallel signal processing system, using DSP Starter Kit(DSK) of which the basic Processor is TMS302C6711 chip. The key ideas of this performance monitor is, using Real Time Data Exchange(RTDX) for the Purpose of real-time data transfer and function of DSP/BIOS, the ability to measure the Performance measure like DSP workload, memory usage, and bridge traffic. In the simulation, FFT, 2D FFT, Matrix Multiplication, and Fir Filter, which are widely used DSP algorithms, have been employed. Using performance monitor and Code Composer Studio from Texas Instrument(Tl) , the result has been recorded according to different frequencies, data sizes, and buffer sizes for a single wave file. The accuracy of our performance monitor has been verified by comparing those recorded results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.669-678
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• 2018

This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.570-581
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• 2015

In recent years, many institutions predict that cloud services and big data will be popular IT trends in the near future. A number of leading IT vendors are focusing on practical solutions and services for cloud and big data. In addition, cloud has the advantage of unrestricted in selecting resources for business model based on a variety of internet-based technologies which is the reason that provisioning and virtualization technologies for active resource expansion has been attracting attention as a leading technology above all the other technologies. Big data took data prediction model to another level by providing the base for the analysis of unstructured data that could not have been analyzed in the past. Since what cloud services and big data have in common is the services and analysis based on mass amount of data, efficient operation and designing of mass data has become a critical issue from the early stage of development. Thus, in this paper, I would like to establish data processing architecture based on technological requirements of mass data for cloud and big data services. Particularly, I would like to introduce requirements that must be met in order for distributed file system to engage in cloud computing, and efficient compression technology requirements of mass data for big data and cloud computing in terms of cost-saving, as well as technological requirements of open-source-based system such as Hadoop eco system distributed file system and memory database that are available in cloud computing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.292-294
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• 2018

Recently, damage caused by natural disasters such as fire, earthquake, heavy rains and heavy snow is increasing. In addition, traffic accidents due to freezing, fog and fire in tunnels and bridges are frequently occurring. In such a disaster situation, it is very important to take prompt action by the person in charge of managing the facility and area.To this end, a disaster broadcasting system is used, but in the existing system, the broadcasting room and the speaker are connected by a wired connection. Also, the person in charge has to be in the broadcasting room to broadcast, which has a problem of delaying the time. In this paper, we design a disaster broadcasting system using LTE modem. The designed system enables a broadcasting person to make a call to a broadcasting system from anywhere using a cellular phone and a public telephone. Broadcasting via telephone is possible only with the telephone number pre-registered in the system and can be registered / deleted by the administrator. The registered telephone number, incoming voice file, and announcement voice for automatic broadcasting are stored in the system internal SD memory for convenient management. This disaster broadcasting system is expected to contribute to quick and convenient disaster broadcasting.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.381-385
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• 2010

An aging Society solitary life old mans are increasing. The nurses have to visit old mans and must confirm their disease, because they do not act well. It is very difficult to take care old man, because the number of Nurses are small. This problem is solved by collection of data about condition of old mans from long distance. Data communication with Ethernet have benefit to collection of measurement of old man's condition. The Data storage system an long distance place are storaged data and after several day data was transmitted to the DB over the Ethernet. For Miniaturization of such system the system must be OS-less Embedded Ethernet Server system. Such system manages the file management system only with H/W. The Storage device is used SD-card. SD Card is small size and operates with small power. By using 512MB sd memory card, it is possible to storage during 5~6 years, 10 byte of temperature value per second. In this paper, we make a Embedded Ethernet Server using W3100A, Atmega128 MCU and data stroage device using SD-Card. This system operates with O/S-less Embedded Ethernet Server. We talk about file System, Storage and Ethernet. We explained about MCU Atmega128, Interface between LAN LSIand W3100A, Interface between W3100A and Phyceiver RTL8201, data I/O between MCU and SD-Card and File System. We shows the experiment device and result of monitoring.

• Convergence Security Journal
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• v.6 no.3
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• pp.1-12
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• 2006

Malicious codes have been widely documented and detected in information security breach occurrences of Microsoft Windows platform. Legacy information security systems are particularly vulnerable to breaches, due to Window kernel-based malicious codes, that penetrate existing protection and remain undetected. To date there has not been enough quality study into and information sharing about Windows kernel and inner code mechanisms, and this is the core reason for the success of these codes into entering systems and remaining undetected. This paper focus on classification and formalization of type target and mechanism of various Windows kernel-based attacks, and will present suggestions for effective response methodologies in the categories of, "Kernel memory protection", "Process & driver protection" and "File system & registry protection". An effective Windows kernel protection system will be presented through the collection and analysis of Windows kernel and inside mechanisms, and through suggestions for the implementation methodologies of unreleased and new Windows kernel protection skill. Results presented in this paper will explain that the suggested system be highly effective and has more accurate for intrusion detection ratios, then the current legacy security systems (i.e., virus vaccines and Windows IPS, etc) intrusion detection ratios. So, It is expected that the suggested system provides a good solution to prevent IT infrastructure from complicated and intelligent Windows kernel attacks.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.1-12
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• 2003

Recently, there have been many indexing schemes for multimedia data such as image, video data. But recent database applications, for example data mining and multimedia database, are required to support multi-user environment. In order for indexing schemes to be useful in multi-user environment, a concurrency control algorithm is required to handle it. So we propose a concurrency control algorithm that can be applied to CBF (cell-based filtering method), which uses the signature of the cell for alleviating the dimensional curse problem. In addition, we extend the SHORE storage system of Wisconsin university in order to handle high-dimensional data. This extended SHORE storage system provides conventional storage manager functions, guarantees the integrity of high-dimensional data and is flexible to the large scale of feature vectors for preventing the usage of large main memory. Finally, we implement the web-based image retrieval system by using the extended SHORE storage system. The key feature of this system is platform-independent access to the high-dimensional data as well as functionality of efficient content-based queries. Lastly. We evaluate an average response time of point query, range query and k-nearest query in terms of the number of threads.