• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3533-3549
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• 2019

A big database utilizes the establishing network technology, and it became an emerging trend in the computing field. Therefore, there is a necessity for an optimal and effective data distribution approach to deal with this trend. This research presents the practical perspective of designing and implementing distributed database features. The proposed system has been establishing the satisfying, reliable, scalable, and standardized use of information. Furthermore, the proposed scheme reduces the vast and recurring efforts for designing an individual system for each university, as well as it is effectively participating in solving the course equivalence problem. The empirical finding in this study shows the superiority of the distributed system performance based on the average response time and the average waiting time than the centralized system. The system throughput also overcomes the centralized system because of data distribution and replication. Therefore, the analyzed data shows that the centralized system thrashes when the workload exceeds 60%, while the distributed system becomes thrashes after 81% workload.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.389-401
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• 2022

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.391-400
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• 2017

Geo-based application services linked with the Open Geospatial Consortium (OGC) Web Processing Service (WPS) protocol have been regarded as an important standardized framework for of digital earth building in the web environments. The WPS protocol provides interface standards for analysis functionalities within geo-spatial processing in web-based service systems. Despite its significance, there is few performance tests of WPS applications. The main motivation in this study is to perform the comparative performance test on WPS standards. Test system, which was composed of WPS servers, WPS framework, data management module, geo-based data processing module and client-sided system, was implemented by fully open source stack. In this system, two kinds of geo-based image processing functions such as cloud detection and gradient magnitude computation were applied. The performance test of different server environments of non-WPS, synchronous WPS 1.0 and asynchronous WPS 2.0 was carried out using 100 threads and 400 threads corresponds client users on a web-based application service. As the result, at 100 threads, performance of three environments was within an adjacent range in the average response time to complete the processing of each thread. At 400 threads, the application case of WPS 2.0 showed the distinguished characteristics for higher performance in the response time than the small threads cases. It is thought that WPS 2.0 contributes to settlement of without performance problems such as time delay or thread accumulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.208-213
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• 2016

In the fourth industrial revolution, customization is becoming a conversation topic in various domains. Industry 4.0 applies cyber-physical systems (CPS), the Internet of Things (IoT), and cloud computing to manufacturing businesses. One of the main phrases in Industry 4.0 is mass customization. Optimized products or services are developed and provided through customization. Therefore, the competitiveness of a product can be enhanced, and satisfaction is improved. In particular, as IoT technology spreads, customization is an essential aspect of smooth service connections between various devices or things. Customized services in mobile applications are assembled and operate in various mobile devices in the mobile environment. Therefore, this paper proposes a method for improving customized cloud server-based mobile architectures, processes, and metrics, and for measuring the performance improvement of the customized architectures operating in various mobile devices based on the Android or IOS platforms. We reduce the total time required for customization in half as a result of applying the proposed customized architectures, processes, and metrics in various devices.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.11
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• pp.263-270
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• 2019

Vehicular cloud computing is a new emerging technology that can provide drivers with cloud services to enable various vehicular applications. A vehicular cloud is defined as a set of vehicles that share their own resources. Vehicles should collaborate with each other to construct vehicular clouds through vehicle-to-vehicle communications. Since collaborating vehicles to construct the vehicular cloud have different speeds, directions and locations respectively, the vehicular cloud is constructed in multi-hop communication range. Due to intermittent wireless connectivity and low density of vehicles with the limited resources, the construction of vehicular cloud with multi-hop communications has become challenging in vehicular environments in terms of the service success ratio, the service delay, and the transmitted packet number. Thus, we propose a multi-hop vehicular cloud construction protocol that increases the service success ratio and decreases the service delay and the transmitted packet number. The proposed protocol uses a connection time-based intermediate vehicle selection scheme to reduce the cloud failure probability of multi-hop vehicular cloud. Simulation results conducted in various environments verify that the proposed protocol achieves better performance than the existing protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.287-307
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• 2018

There are two targets to schedule parallel jobs in the Cloud: (1) scheduling the jobs as many as possible, and (2) reducing the average execution time of the jobs. Most of previous work mainly focuses on the computing speed of resources without considering other attributes, such as bandwidth, memory and so on. Especially, past work does not consider the supply-demand condition from those attributes. Resources have different attributes, considering those attributes together makes the scheduling problem more difficult. This is the problem that we try to solve in this paper. First of all, we propose a new parallel job scheduling method based on a classification method of resources from different attributes, and then a scheduling method-CPLMT (Cloud parallel scheduling based on the lists of multiple attributes) is proposed for the parallel tasks. The classification method categories resources into different kinds according to the number of resources that satisfy the job from different attributes of the resource, such as the speed of the resource, memory and so on. Different kinds have different priorities in the scheduling. For the job that belongs to the same kinds, we propose CPLMT to schedule those jobs. Comparisons between our method, FIFO (First in first out), ASJS (Adaptive Scoring Job Scheduling), Fair and CMMS (Cloud-Minmin) are executed under different environments. The simulation results show that our proposed CPLMT not only reduces the number of unfinished jobs, but also reduces the average execution time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.678-680
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• 2013

Recently, A computing environment are provided that can easily be used for services based on the cloud environment. Among them, SaaS(SoftWare as a Service) is that it provides cloud users to be available by placing the cloud systems on the Internet software. But, the problem with this, problems is that user can not be utilized to not find a service registered in the cloud system. The thing to make clear the meaning and relationship between services using the ontology to solve these problems, It must be supported to be used to find the exact service the user wants. Ontology for service discovery can be used to help to find services by guessing relevance by using the function or service names entered by the user. We provide how to configure the service ontology and the search system of services using ontology.

• Journal of Information Technology Applications and Management
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• v.26 no.5
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• pp.57-65
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• 2019

Recommendation Systems are information technologies that E-commerce merchants have adopted so that online shoppers can receive suggestions on items that might be interesting or complementing to their purchased items. These systems stipulate valuable assistance to the user's purchasing decisions, and provide quality of push service. Traditionally, Recommendation Systems have been designed using a centralized system, but information service is growing vast with a rapid and strong scalability. The next generation of information technology such as Cloud Computing and Big Data Environment has handled massive data and is able to support enormous processing power. Nevertheless, analytic technologies are lacking the different capabilities when processing big data. Accordingly, we are trying to design a conceptual service model with a proposed new algorithm and user adaptation on dynamic recommendation service for big data environment.

• Annual Conference of KIPS
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• 2012.04a
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• pp.818-821
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• 2012

건설CALS 시스템은 건설사업의 전 과정에서 발생되는 방대한 정보를 관리 제공하는 정보시스템으로 건설CALS 포탈 및 항만건설통합정보 등 6개 단위 시스템으로 구성되어 있다. 그러나 각 시스템들의 개발 시기가 개별적이고 하드웨어 구성 또한 독립적으로 이루어져 신규 시스템 추가 시 기존 시스템과의 연계가 어려우며 별도 하드웨어 및 소프트웨어를 추가하여야 한다. 또한, 시스템 운영 중 발생한 유휴자원을 다른 시스템에서 활용하지 못하기 때문에 시스템 운영 측면에서 비효율적이다. 이에 본 논문에서는 클라우드 컴퓨팅 기반 건설CALS 시스템 아키텍처를 설계하였다. 설계한 아키텍처는 시스템 확장이 용이하고 자원에 대한 동적 할당과 더불어 잉여 자원에 대한 높은 활용성, 시스템 가용성을 증대 시킬 수 있어 효율적인 시스템 운영이 가능하다.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.75-82
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• 2022

Medical data is one of the data that must be kept in safe containers, far from intrusion, viewing and modification. With the technological developments in hospital systems and the use of cloud computing, it has become necessary to save, encrypt and even hide data from the eyes of attackers. Medical data includes medical images, whether they are x-ray images of patients or others, or even documents that have been saved in the image format. In this review, we review the latest research and the latest tools and algorithms that are used to protect, encrypt and hide these images, and discuss the most important challenges facing these areas.