• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.2
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• pp.102-113
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• 2014

Present communication and network environment have been moving rapidly toward wireless and mobile base from existing wired internet base. This change of trend influences greatly on business methods accordingly. Therefore many enterprises are trying hard to adopt mobile business in order to gain competitive edge of their products and they are in need of more effective and stable mobile solutions. However, the method of establishing optimal mobile computing environment and how to handle existing business process and use vast amount of database are still needed. Therefore this paper tries to realize a mobile middleware system as a mobile business establishment supporting tool that could link various computational resource on wired internet with wireless LAN, mobile phone network, and mobile devices. To accomplish that specific goal, this paper provides a powerful tool of mobile and wireless application data access that could expand the line of business already set up in general enterprises easily and rapidly into mobile environment. When this suggested solution is applied in the field of industry, it can economically change legacy business process into mobile environment without having to change existing logic and resources at all.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.1-8
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• 2021

With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.296-309
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• 2003

One of commercial applications of mobile computing is ATIS(Advanced Traveler Information Systems) in ITS(Intelligent Transport Systems). In ATIS, a primary mobile computing task is to compute the shortest path from the current location to the destination. In this paper, we have studied the shortest path re-computation problem that arises in the DRGS(Dynamic Route Guidance System) in ATIS where the cost of topological digital road map is frequently updated as traffic condition changes dynamically. Previously suggested methods either re-compute the shortest path from scratch or re-compute the shortest path just between the two end nodes of the edge where the cost change occurs. However, these methods we trivial in that they do not intelligently utilize the previously computed shortest path information. In this paper, we propose an efficient approximate shortest path re-computation method based on the dynamic window scheme. The proposed method re-computes an approximate shortest path very quickly by utilizing the previously computed shortest path information. We first show the theoretical analysis of our methods and then present an in-depth experimental performance analysis by implementing it on grid graphs as well as a real digital road map.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.794-815
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• 2023

The rapid development of mobile communication not only has made the industry gradually diversified, but also has enhanced the service quality requirements of users. In this regard, it is imperative to consider jointly network slicing and mobile edge computing. The former mainly ensures the requirements of varied vertical services preferably, and the latter solves the conflict between the user's own energy and harsh latency. At present, the integration of the two faces many challenges and need to carry out at different levels. The main target of the paper is to minimize the energy consumption of the system, and introduce a multi-slice joint task offloading and resource allocation scheme for massive multiple input multiple output enabled heterogeneous networks. The problem is formulated by collaborative optimizing offloading ratios, user association, transmission power and resource slicing, while being limited by the dissimilar latency and rate of multi-slice. To solve it, assign the optimal problem to two sub-problems of offloading decision and resource allocation, then solve them separately by exploiting the alternative optimization technique and Karush-Kuhn-Tucker conditions. Finally, a novel slices task offloading and resource allocation algorithm is proposed to get the offloading and resource allocation strategies. Numerous simulation results manifest that the proposed scheme has certain feasibility and effectiveness, and its performance is better than the other baseline scheme.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.623-626
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• 2009

New ship technology and trapping equipment must be implemented into ship sailing which is currently used nowadays. The day/night camera stability, user interface, track, and remote control system of Jim structure for all over the world should be competitive in the global market. The development equipment sales are losing its competitiveness edge of the existing sailing ship communications equipment due to supply to the aging of the entire system and integration of the development especially for foreign equipment competitor.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.31-48
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• 2023

The popularization of smart devices and subsequent optimization of their sensing capacity has resulted in a novel mobile crowdsensing (MCS) pattern, which employs smart devices as sensing nodes by recruiting users to develop a sensing network for multiple-task performance. This technique has garnered much scholarly interest in terms of sensing range, cost, and integration. The MCS is prevalent in various fields, including environmental monitoring, noise monitoring, and road monitoring. A complete MCS life cycle entails task allocation, data collection, and data aggregation. Regardless, specific drawbacks remain unresolved in this study despite extensive research on this life cycle. This article mainly summarizes single-task, multi-task allocation, and space-time multi-task allocation at the task allocation stage. Meanwhile, the quality, safety, and efficiency of data collection are discussed at the data collection stage. Edge computing, which provides a novel development idea to derive data from the MCS system, is also highlighted. Furthermore, data aggregation security and quality are summarized at the data aggregation stage. The novel development of multi-modal data aggregation is also outlined following the diversity of data obtained from MCS. Overall, this article summarizes the three aspects of the MCS life cycle, analyzes the issues underlying this study, and offers developmental directions for future scholars' reference.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.51-54
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• 2021

본 논문은 차량과 보행자 간 충돌 사고를 예측하는 V2P(Vehicle to Pedestrian) 서비스에서 보행자 휴대기기의 데이터 전송 시점을 동적으로 계산함으로써 불필요한 통신을 감소시켜 에너지 효율을 향상시키는 것을 목적으로 하며, MEC(Mobile Edge Computing) 기반 V2P 서비스를 제안하였다. V2P 서비스에서는 보행자와 차량 간 충돌 가능성을 예측하기 위하여 두 객체의 실시간 GPS 데이터가 요구된다. 이때 보편적으로 보행자에 비해 차량의 이동속도가 더 빠르기 때문에 보행자가 빠르게 이동해 들어오는 주변 차량에 발견될 수 있기 위해서는 자신의 위치에는 의미 있는 변화가 발생하지 않았더라도 차량 이동속도에 맞춘 빠른 주기로 차량 혹은 중앙 클라우드 서버로 자신의 데이터를 송신해야만 한다. 이 과정에서 보행자 휴대폰의 에너지가 급속하게 소모된다. 따라서 본 연구는 이러한 문제를 해결하기 위하여 MEC 서버를 배치한 V2P 서비스를 제안하였고, 보행자가 본인의 상태 정보를 활용하여 효율적인 다음 데이터 전송 시점을 계산할 수 있는 동적시점계산 알고리즘을 제안하였다.

• ETRI Journal
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• v.40 no.3
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• pp.318-329
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• 2018

Femtocell (FC) technology envisaged as a cost-effective approach to attain better indoor coverage of mobile voice and data service. Deployment of FCs over macrocell forms a heterogeneous network. In urban areas, the key factor limits the successful deployment of FCs is inter-cell interference (ICI), which severely affects the performance of victim users. Autonomous FC transmission power setting is one straightforward way for coordinating ICI in the downlink. Application of intelligent control using soft computing techniques has not yet explored well for wireless networks. In this work, autonomous FC transmission power setting strategy using Adaptive Neuro Fuzzy Inference System is proposed. The main advantage of the proposed method is zero signaling overhead, reduced computational complexity and bare minimum delay in performing power setting of FC base station because only the periodic channel measurement reports fed back by the user equipment are needed. System level simulation results validate the effectiveness of the proposed method by providing much better throughput, even under high interference activation scenario and cell edge users can be prevented from going outage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1666-1672
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• 2016

In recent years, smart technology has been applied to various information system fields. Especially, traditional library service area is changing to Smart-Library from Digital-Library. In this environment are need to library service software platform for supporting variety content, library services, users and smart-devices. Due to this, existing library service has a limitation that inhibits semantic interoperability between different heterogeneous library systems. In this paper, we propose Linked-Open-Data based smart library as an archetype of future-library system that provide a variety content and system interaction and integration of services. It is an innovative system of the cutting-edge information intensive. Therefore, we designed system environments according to various integration requirements for smart library based on Linked-Open-Data. And, we describe the functional requirements of smart-library systems by considering the users' demands and the eco-systems of information technology. In addition, we show the reference framework, which can accommodate the functional requirements and provide smart knowledge service to user through a variety of smart-devices.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.29-37
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• 2015

In this paper, we propose a robust pre-processing module for camera-based Optical Music Score Recognition (OMR) on mobile device. The captured images likely suffer for recognition from many distortions such as illumination, blur, low resolution, etc. Especially, the complex background music sheets recognition are difficult. Through any symbol recognition system, the staff line height and staff line space are used many times and have a big impact on recognition module. A robust and accurate staff line height and staff line space are essential. Some staff line height and staff line space are proposed for binary image. But in case of complex background music sheet image, the binarization results from common binarization algorithm are not satisfactory. It can cause incorrect staff line height and staff line space estimation. We propose a robust staff line height and staff line space estimation by using run-length encoding technique on edge image. Proposed method is composed of two steps, first step, we conducted the staff line height and staff line space estimation based on edge image using by Sobel operator on image blocks. Each column of edge image is encoded by run-length encoding algorithm Second step, we detect the staff line using by Stable Path algorithm and removal the staff line using by adaptive Line Track Height algorithm which is to track the staff lines positions. The result has shown that robust and accurate estimation is possible even in complex background cases.