• The KIPS Transactions:PartA
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• v.8A no.3
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• pp.235-244
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• 2001

Development of network and computer technology results in many studies to use physically distributed computers as a single resource. Generally, these studies have focused on developing environments based on message passing. These environments are mainly used to solve problems for scientific computation and process in parallel suing inside parallelism of the given problems. Therefore, these environments provide high parallelism generally, while it is difficult to program and use as well as it is required to have user accounts in the distributed computers. If a given problem is divided into completely independent subproblems, more efficient environment can be provided. We can find these problems in bio-informatics, 3D animatin, graphics, and etc., so the development of new environment for these problems can be considered to be very important. Therefore, we suggest new environment called InterCom based on a proxy computing, which can solve these problems efficiently, and explain the implementation of this environment. This environment consists of agent, server, and client. Merits of this environment are easy programing, no need of user accounts in the distributed computers, and easiness by compiling distributed code automatically.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5B
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• pp.413-420
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• 2006

HMIPv6 is designed to reduce the signaling load to external network and improve handover speed of MN by including Mobility Anchor Point(MAP) in local handover. However in this case of macro handover, it's just used pervious MIPv6 handover algorithm. So, it occurs packet loss and transmission delay problem. In this paper, we propose the mechanism applying the HMIPv6 for Fast Handover to choose suitable to the condition buffering handover. The condition for the selection is result distance measurement between MN and CN, between MN and NAR. Furthermore, using F-SNOOP protocol, it is possible to improve wireless network performance. Wireless network has high Bit Error Rate(BER) characteristic because of path loss, fading, noise and interference. TCP regards such errors as congestion and starts congestion control. This congestion control makes packet transmission rate low. However, F-SNOOP improves TCP performance based on SNOOP and Freeze TCP that use Zero Window Advertisement(ZWA) message when handoff occurs in wireless network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.10
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• pp.938-946
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• 2012

Interference alignment (IA) is a data transmission technique that achieves the maximum degrees-of-freedom (DoF) in the multiuser interference channel for high signal-to-noise ratios (SNRs). However, most prior works on IA are based on the unrealistic assumption that perfect and global channel-state information (CSI) is available at all transmitters and receivers. In this paper, we propose the efficient design of feedback framework for IA that substantially suppresses the feedback overhead. While the feedback overhead in the conventional IA quadratically increases with K, the proposed feedback scheme supports the sequential exchange of computed IA precoders between transmitters and receivers and reduces the feedback overhead that linearly scales with K. Moreover, we analyze the residual interference due to the quantization error in limited feedback and propose the ordered IA algorithm that selects IA pair to minimize the sum residual interference in given channel realizations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.950-958
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• 2007

This paper presents an efficient packet loss resilient scheme for real-time video transmission over the Internet. By analyzing the temporal and spatial dependencies in inter- and intra-frames, we assign forward error correction codes (FEC) across video packets for minimizing the effect of error concealment and error propagation from packet loss. To achieve optimal allocation of FEC codes, we formulate the effect of packet loss on video quality degradation as packet distortion model. Then we propose an unequal FEC assignment scheme with low complexity based on packet correction rate, which uses the packet distortion model and includes channel status information. Simulation results show that the proposed FEC assignment scheme gives substantial improvement for the received video quality in packet lossy networks. Furthermore the proposed scheme achieves relatively smaller degradation of video quality with higher packet loss rates.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.631-636
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• 2010

With the growing trends of communication- broadcasting convergence, a hybrid IPTV that supports both IP network-based on-demand media and terrestrial or cable-based broadcast media is gaining attraction. This paper proposes a rich media framework for hybrid IPTV with support of the latest H.264 codec. For this purpose, we design and implement a media component and a RIA run-time engine customized for TV with the hybrid media. The media component has been designed to provide a uniform and efficient application interface to the various playback methods for RF broadcast and IP-based stored or live media. For performance and portability, it exploits media stream abstraction, adaptive on-demand I-frame search, and automatic calculation of play duration. Based on the proposed media interface, we develop a RIA run-time prototype. It has been carefully designed to fully utilize the built-in graphic acceleration hardware for optimized rendering in the resource-constrained IPTV environments. Demonstration and experiment results validate the performance and usefulness of the developed framework. The framework is expected to be used effectively to support graphics and hybrid media in the applications of IPTV-based VOD, advertisement, and education.

• Journal of KIISE
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• v.44 no.7
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• pp.703-709
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• 2017

Outsourcing databases is to offload storage and computationally intensive tasks to the third party server. Therefore, data owners can manage big data, and handle queries from clients, without building a costly infrastructure. However, because of the insecurity of network systems, the third-party server may be untrusted, thus the query results from the server may be tampered with. This problem has motivated significant research efforts on authenticating various queries such as range query, kNN query, function query, etc. Although aggregation queries play a key role in analyzing big data, authenticating aggregation queries has not been extensively studied, and the previous works are not efficient for data with high dimension or a large number of distinct values. In this paper, we propose the AMR-tree that is a data structure, applied to authenticate aggregation queries. We also propose an efficient proof construction method and a verification method with the AMR-tree. Furthermore, we validate the performance of the proposed algorithm by conducting various experiments through changing parameters such as the number of distinct values, the number of records, and the dimension of data.

• Journal of the Korea Computer Industry Society
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• v.3 no.2
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• pp.209-216
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• 2002

World Wide Web has potential possibility of infrastructure for parallel computing environment connecting massive computing resources, not just platform to provide and share information via browser. The approach of Web-based parallel computing has many advantages of the ease of accessibility, scalability, cost-effectiveness, and utilization of existing networks. Applet has the possibility of decomposing the independent/parallel task, moving over network, and executing in computers connected in Web, but it lacks in the flexibility due to strict security semantic model. Therefore, in this paper, Web-based parallel computing environment using mobile agent, Aglet (Agile applet) was designed and possible implementation technologies and architecture were analyzed. And simple simulation and analysis was done compared with applet-based approach.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.249-261
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• 2014

Ever increasing "Big data" can only be effectively processed by parallel computing. Parallel computing refers to a high performance computational method that achieves effectiveness by dividing a big query into smaller subtasks and aggregating results from subtasks to provide an output. However, it is well-known that parallel computing does not achieve scalability which means that performance is improved linearly by adding more computers because it requires a very careful assignment of tasks to each node and collecting results in a timely manner. Hadoop is one of the most successful platforms to attain scalability. In this paper, we propose a measurement for Hadoop optimization by utilizing a Lorenz curve which is a proxy for the inequality of hardware resources. Our proposed index takes into account the intrinsic overhead of Hadoop systems such as CPU, disk I/O and network. Therefore, it also indicates that a given Hadoop can be improved explicitly and in what capacity. Our proposed method is illustrated with experimental data and substantiated by Monte Carlo simulations.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.117-127
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• 2009

This study analyzed the uncertainty of the forecasted link traffic flow, and estimated of the interval link flow using Korea Transport Data Base (KTDB) to consider those risks into the feasibility study. In the paper, the uncertainty was analyzed according to the stochastic variation of the KTDB origin-destination traffic. It was found that the uncertainty of the entire network traffic forecasts was 15.4% in average,. when the stochastic variation of the KTDB was considered. The results showed that the more congested the roads were, the bigger the uncertainty of forecasted link traffic flow were found. In particular, we estimated the variance of the forecasted traffic flow, and suggested interval estimates of the forecasted traffic flow instead of point estimates which were presented in the common feasibility studies. These results are expected to contribute the quantitative evaluation of uncertain road investment projects and to provide valuable information to the decision makers for the transport investment.

• Journal of Wetlands Research
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• v.12 no.3
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• pp.79-97
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• 2010

The purpose of this research is to apply the neural networks models for the hydrologic disaggregation of the yearly pan evaporation(PE) data in Republic of Korea. The neural networks models consist of multilayer perceptron neural networks model(MLP-NNM) and support vector machine neural networks model(SVM-NNM), respectively. And, for the evaluation of the neural networks models, they are composed of training and test performances, respectively. The three types of data such as the historic, the generated, and the mixed data are used for the training performance. The only historic data, however, is used for the testing performance. The application of MLP-NNM and SVM-NNM for the hydrologic disaggregation of nonlinear time series data is evaluated from results of this research. Four kinds of the statistical index for the evaluation are suggested; CC, RMSE, E, and AARE, respectively. Homogeneity test using ANOVA and Mann-Whitney U test, furthermore, is carried out for the observed and calculated monthly PE data. We can construct the credible monthly PE data from the hydrologic disaggregation of the yearly PE data, and the available data for the evaluation of irrigation and drainage networks system can be suggested.