• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.1-16
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• 2012

Cost-effective mobility management for the roaming mobile users is very important in the seamless services on next-generation wireless network (NGWN). MIPv6 (Mobile IPv6) is one of the mobility management schemes proposed by the IETF (The Internet Engineering Task Force) and various IPv6-based mobility management schemes have been developed. They are directly involved with data transfer from MN (Mobile Node). In this paper, two kinds of schemes in analyzing of mobility management schemes are proposed. The signaling transfer and packet delivery procedures for each mobility management schemes are analyzed, respectively. The signaling cost for mobility management schemes are calculated, and the cost of each protocol are analyzed numerically. In other word, applying the sum of signaling cost and packet delivery cost to each mobility management scheme, their costs are analyzed. Finally, our performance evaluation results that the network-based mobility management scheme shows better performance in terms of overall cost.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.421-433
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• 2012

AMGA service, which is one of the EMI gLite middleware components, is widely used for analysis of distributed large scale experiments data as metadata repository by scientific and technological researchers and the use of AMGA is extended farther to include general industries needing metadata Catalogue as well. However AMGA, based unix and Grid UI, has the weakness of being absence of general-purpose user interfaces in comparison to other commercial database systems and that's why it's difficult to use and diffuse it although it has the superiority of the functionality. In this paper, we developed AMGA GUI toolkit to provide work convenience using object-oriented modeling language(UML). Currently, AMGA has been used as the main component among many user communities such as Belle II, WISDOM, MDM, and so on, but we expect that this development can not only lower the barrier to entry for AMGA beginners to use it, but lead to expand the use of AMGA service over more communities.

• Journal of KIISE
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• v.44 no.8
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• pp.782-790
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• 2017

The service, 'Hot Search Keywords', provides a list of the most hot search terms of different web services such as Naver or Daum. The service, bases the changes in rank of a specific search keyword on changes in its users' interest. This paper introduces a temporal modelling framework for predicting the rank change of hot search keywords using past rank data and machine learning. Past rank data shows that more than 70% of hot search keywords tend to disappear and reappear later. The authors processed missing rank value, using deletion, dummy variables, mean substitution, and expectation maximization. It is however crucial to calculate the optimal window size of the past rank data. We proposed an optimal window size selection approach based on the minimum amount of time a topic within the same or a differing context disappeared. The experiments were conducted with four different machine-learning techniques using the Naver, Daum, and Nate 'Hot Search Keywords' datasets, which were collected for 2 years.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.83-90
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• 2016

In this paper, we performed the analysis of transmission performance for Collision Free Period(CFP) supported by the low-power communication technology, IEEE 802.15.4 MAC (Media Access Control). For the analysis, periodic traffic, original service target of CFP, is considered and, according to the Quality of Service required, packet arrival pattern to MAC layer is categorized as batch and non-batch, and analysis on throughput, delay, and energy is performed for those patterns. On the basis of the obtained analysis, performance comparison with Collision Avoidance Period(CAP) is carried out for the health care applications that generate periodic traffic such as Pedometer, ECG, EMG. The evaluation confirms that CFP is more energy efficient for healthcare applications that generate periodic and time-critical traffic and moreover for the application with high bandwidth requirement CFP achieves up to 46% energy savings compared to CAP.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.4
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• pp.246-255
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• 2010

There exist virtual machine scheduling delays in virtualized environment in which virtual machines share physical resources. Many resource management systems have been proposed to provide better application QoS through monitoring and analyzing application performance and resource utilization of virtual machines. However, those management systems don't consider virtual machine scheduling delays, result in incorrect application performance evaluation and QoS violations In this paper, we propose an application behavior analysis considering the scheduling delays, and a virtual machine priority allocation scheme based on the analysis to improve the application response time by minimizing the overall virtual machine scheduling delays.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.739-746
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• 2016

The real-time railway safety monitoring and control system is for prevention of safety accidents, and this system adopts DDS (Data Distribution Service) standard based data transmission method to support integrated management of data from existing on-site safety detection devices. In this paper, we introduce the design of DDS-based data specification from on-site signal equipment on the conventional railway. For this, we (1) design UML data model of KRS SG 0062 standard which defines existing data specification, (2) define DDS Topics for DDS transmission and map KRS model to DDS Topic model, (3) suggest data transformation rules and (4) design network control QoS polices. In addition, we analysis actual on-site log data and validate our data specification design. DDS-based data transmission enables data compatibility among on-site devices and the real-time railway safety monitoring and control system, and allows efficient network management for a large amount of data transfer.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.31-36
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• 2012

In recent years, there has been increasing interest in recommender systems which provide users with personalized suggestions for products or services. In particular, researches of collaborative filtering analyzing relations between users and items has become more active because of the Netflix Prize competition. This paper presents the reinforcement learning approach for collaborative filtering. By applying reinforcement learning techniques to the movie rating, we discovered the connection between a time sequence of past ratings and current ratings. For this, we first formulated the collaborative filtering problem as a Markov Decision Process. And then we trained the learning model which reflects the connection between the time sequence of past ratings and current ratings using Q-learning. The experimental results indicate that there is a significant effect on current ratings by the time sequence of past ratings.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.263-274
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• 2010

To provide context-aware music recommendation service, first of all, we need to catch music mood that a user prefers depending on his situation or context. Among various music characteristics, music mood has a close relation with people‘s emotion. Based on this relationship, some researchers have studied on music mood detection, where they manually select a representative segment of music and classify its mood. Although such approaches show good performance on music mood classification, it's difficult to apply them to new music due to the manual intervention. Moreover, it is more difficult to detect music mood because the mood usually varies with time. To cope with these problems, this paper presents an automatic method to classify the music mood. First, a whole music is segmented into several groups that have similar characteristics by structural information. Then, the mood of each segments is detected, where each individual's preference on mood is modelled by regression based on Thayer's two-dimensional mood model. Experimental results show that the proposed method achieves 80% or higher accuracy.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.791-799
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• 2008

Ansim Flat DATA Plan is a DATA additional service product related to DATA call in a mobile telephone company A. Up to now, the company A is selling it by outbound TM after targeting customers which used data within specific price band. In this paper, we propose a targeting method applying score model combining response rate and retention rate by data mining. The suggested target model is to find customers more likely not only to respond to outbound TM but also to retain Ansim Flat DATA Plan. The proposed targeting method is expected to improve both from 23.7% to 38.8% in the response rate and from 53.2% to 61.4% in the retention rate.

• Spatial Information Research
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• v.22 no.2
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• pp.31-44
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• 2014

According to the purpose of applications, the application program will utilize the most suitable data model and 3D modeling data would be generated based on the selected data model. In these reasons, there are various data sets to represent the same geographical features. The duplicated data sets bring serious problems in system interoperability and data compatibility issues, as well in finance issues of geo-spatial information industries. In order to overcome the problems, this study proposes a spatial data fusion method using topological relationships among spatial objects in the feature classes, called Topological Relation Model (TRM). The TRM is a spatial data fusion method implemented in application-level, which means that the geometric data generated by two different data models are used directly without any data exchange or conversion processes in an application system to provide indoor LBSs. The topological relationships are defined and described by the basic concepts of IndoorGML. After describing the concepts of TRM, experimental implementations of the proposed data fusion method in 3D GIS are presented. In the final section, the limitations of this study and further research are summarized.