• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.9
• /
• pp.445-458
• /
• 2007

This article presents a novel infrastructure for large-memory database processing using commodity hardware with operating system support. We exploit inexpensive PCs and a high-speed network capable of Remote Direct Memory Access (RDMA) operations to build a new memory hierarchy between fast volatile memory and slow disk storage. The new memory hierarchy guarantees a reasonable response time, and its storage size enables us to run large-memory database systems with little performance degradation. The proposed architecture has two main components: (1) a remote memory system inside the Linux kernel to manage other computers' memory pages efficiently and (2) a remote memory pager responsible for manipulating remote read/write operations on remote memory pages. We insist that the proposed architecture is practical enough to support the rigorous demands of commercial in-memory database systems by demonstrating the performance of publicly available main-memory databases (e.g., MySQL) on our prototyped system. The experimental results show very interesting results from the TPC-C benchmark.

• The Journal of the Korea Contents Association
• /
• v.9 no.2
• /
• pp.76-87
• /
• 2009

The growth of CPU and communication technologies have made an important contribution to the development of the network-based intelligent service robots. Robot software must guarantee the correct execution and safety of the user. To achieve this, it is highly required to research how to guarantee the QoS of the components which organize a robot software. The QoS of robot components aims to execute the component stably by processing the data stream in a correct way. By guaranteeing QoS, we can achieve the intelligence and stability of robots. In this paper, we design and implement the QoS framework to guarantee the QoS of robot components on robot platforms with limited resources. We also measure the response times of QoS requests and present the performance analysis results about it.

• KIPS Transactions on Software and Data Engineering
• /
• v.1 no.3
• /
• pp.169-176
• /
• 2012

The information delivery and transmission media(DID or PID) market is making remarkable growth as the high-speed networks are spreading and LCD/LED TVs are more and more popularized, and display devices are increasingly large and high-definition. In addition, the popularization of smart devices and the expansion of the information delivery and transmission media market make a demand for N-Screen in content service. Colleges and universities have installed and operated various types of DID to promote their schools and departments and deliver information about them, still remaining in the level of media content implementation. So, we implement and evaluate a next-generation electronic bulletin board for each department that allows for interactive N-Screen communication based on the integration of smart phone and internet. This board enhanced efficiency as supporting N-Screen, inserting and deleting the contents at real time and offering bidirectional communication.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.4
• /
• pp.121-130
• /
• 2004

In the application requiring the interoperability of different networks such as VoIP and wireless communication system, two speech codecs must work together with the structure of cascaded connection, tandem. Tandem has several problems such as long delay, high complexity and quality degradation due to twice complete encoding/decoding process. Transcoding is one of the best solutions to solve these problems. Transcoding algorithm is varied with the structure of source and target coder. In this paper, transcoding algorithm including the LSP conversion, the pitch estimation and new perceptual weighting filter for reducing complexity and improving qualify is proposed. These algorithms are applied to the pair of AMR md G.723.1. By employing the proposed algorithms in the transcoder, the complexity is reduced by about 20%-58% and quality is improved compared to tandem.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.1A
• /
• pp.1-10
• /
• 2006

The Home Phoneline Networking Alliance(HomePNA) 2.0 technology can establish a home network using existing in-home phone lines, which provides a channel rate of 4-32 Mbps. HomePNA 2.0 Medium Access Control(MAC) protocol adopts an IEEE 802.3 Carrier Sense Multiple Access with Collision Detection(CSMA/CD) access method, Quality of Service(QoS) algorithm, and Distributed Fair Priority Queuing(DFPQ) collision resolution algorithm. In this paper, we describe some performance analysis results of HomePNA 2.0 MAC protocol and the requirements of HomePNA 2.0 MAC controller. Then, we propose the architecture of HomePNA 2.0 MAC controller circuit, show the simulation result of each block included in HomePNA 2.0 MAC controller, and present the HomePNA 2.0 transceiver chip that we have implemented.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.1
• /
• pp.53-60
• /
• 2017

This paper is to design and implement the drone that supports a wideband multimedia communication and a long-range to save people in maritime. The drone is an Unnamed Aerial Vehicle (UAV) that is controlled by a radio wave not by people boarding the machine. We use the drone to respond quickly to the boating accident. To develop a smart drone for the high speed seamless video streaming in a long-range maritime, a necessary techniques are hardware design techniques that design structure of a drone, controlling techniques that operate a drone and communication techniques that control a drone in a long distance. In this paper, the limitations and techniques to design and implement the structure of drone supporting wideband multimedia communication for long-range maritime are explained. By expanding this communication drone network, it is aimed at improving utility of a drone.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.3
• /
• pp.639-652
• /
• 2015

In today's manufacturing environment, the process data can be easily measured and transferred to a computer for analysis in a real-time mode. As a result, it is possible to monitor several correlated quality variables simultaneously. Various multivariate statistical process control (MSPC) procedures have been presented to detect an out-of-control event. Although the classical MSPC procedures give the out-of-control signal, it is difficult to determine which variable has caused the signal. In order to solve this problem, data mining and machine learning techniques can be considered. In this paper, we applied the technique of decision tree learning to the MSPC, and we did simulation for MSPC procedures to monitor the bivariate normal process means. The results of simulation show that the overall performance of the MSPC procedure using decision tree learning technique is similar for several values of correlation coefficient, and the accurate classification rates for out-of-control are different depending on the values of correlation coefficient and the shift magnitude. The introduced procedure has the advantage that it provides the information about assignable causes, which can be required by practitioners.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.182-184
• /
• 2009

FlexRay is a new standard of network communication system which provides a high speed serial communication, time triggered bus and fault tolerant communication between electronic devices for future automotive and ship applications. FlexRay communication controller(CC) is the core of the FlexRay protocol specification. In this paper, we first design the FlexRay CC protocol specification and function parts using SDL(Specification and Description Language). Then, the system is re-designed using Verilog HDL based on the SDL source. The FlexRay CC system was synthesized using Samsung $0.35{\mu}m$ technology. It is shown that the designed system can operate in the frequency range above 80 MHz. In addition, to show the validity of the designed FlexRay system, the FlexRay system is combined with sound source localization system in Robot applications. The combined system is implemented using ALTERA Excalibur ARM EPXA4F672C3. It is shown that the implemented system operates successfully.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.41 no.6 s.324
• /
• pp.33-39
• /
• 2004

Design of efficient Medium Access Control (MAC) protocols with both high throughput performances is a major focus in distributed contention based MAC protocol research. In this paper, we propose an efficient contention based MAC protocol for wireless Local Area Networks, namely, the Developed Collision Resolution (DCR) algorithm. This algorithm is developed based on the following innovative ideas: to speed up the collision resolution, we actively redistribute the backoff timers for all active nodes; to reduce the average number of idle slots, we use smaller contention window sizes for nodes with successful packet transmissions and reduce the backoff timers exponentially fast when a fixed number of consecutive idle slots are detected. We show that the proposed DCR algorithm provides high throughput performance and low latency in wireless LANs.

• The Korean Journal of Applied Statistics
• /
• v.29 no.6
• /
• pp.1107-1116
• /
• 2016

Recent astronomical survey observations have produced substantial amounts of data as well as completely changed conventional methods of analyzing astronomical data. Both classical statistical inference and modern machine learning methods have been used in every step of data analysis that range from data calibration to inferences of physical models. We are seeing the growing popularity of using machine learning methods in classical problems of astronomical data analysis due to low-cost data acquisition using cheap large-scale detectors and fast computer networks that enable us to share large volumes of data. It is common to consider the effects of inhomogeneous spatial and temporal coverage in the analysis of big astronomical data. The growing size of the data requires us to use parallel distributed computing environments as well as machine learning algorithms. Distributed data analysis systems have not been adopted widely for the general analysis of massive astronomical data. Gathering adequate training data is expensive in observation and learning data are generally collected from multiple data sources in astronomy; therefore, semi-supervised and ensemble machine learning methods will become important for the analysis of big astronomical data.