• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.149-152
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• 1998

Nowadays, GIS, as multi-discipline information system, is closely linked with GPS application in conjunction with GIS-T or Logistics GIS. With this R&D trend. CPS/GIS application system for AVL is newly developed in this study. This AVL is designed and implemented by using pure Java computing technology towards com ing Car-equipped wireless Internet PC age, and main features of Java are included at this system: Platform independence, Multi-thread processing, and Object-oriented paradigm. While, because core modules of this AVL are based on GIS spatial engine, unlike other commercial AVLs, large spatial database problem handling digital image/spatial information and attribute information and direct access problem of GIS data is easily dealt with. this system can directly access external database by using JDBC: MS Access for desktop version and Oracle for W/S version. Finally, it is thought that Java-based AVL, one of CPS/CIS applications, can be easily extended into other prospective GIS applications: Land surveyor supporting system, Flight tracking system, 3D facility management system with CPS, and so forth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.670-686
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• 2017

MapReduce (MRV1), a popular programming model, proposed by Google, has been well used to process large datasets in Hadoop, an open source cloud platform. Its new version MapReduce 2.0 (MRV2) developed along with the emerging of Yarn has achieved obvious improvement over MRV1. However, MRV2 suffers from long finishing time on certain types of jobs. Speculative Execution (SE) has been presented as an approach to the problem above by backing up those delayed jobs from low-performance machines to higher ones. In this paper, an adaptive SE strategy (ASE) is presented in Hadoop-2.6.0. Experiment results have depicted that the ASE duplicates tasks according to real-time resources usage among work nodes in a cloud. In addition, the performance of MRV2 is largely improved using the ASE strategy on job execution time and resource consumption, whether in a multi-job environment.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.407-413
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• 2018

In this paper, we present a scalable data delivery infrastructure for such IoT computing environment where we need a common platform where data providers share their diverse sensing data and applications can easily access and receive such data from providers. For efficient data delivery, this paper proposes a new delivery path management technique that take advantage of diverse consumer QoS when building bandwidth-efficient delivery paths. We perform primitive experiments on the path construction and reconstruction which may be major overhead of the scalable infrastructure. The results show that the proposed infrastructure achieves a high level of scalability, and demonstrates that the management overhead is not significant.

• Journal of IKEEE
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• v.19 no.2
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• pp.276-281
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• 2015

Engineers increasingly rely on computers and their computer programming skills for their works. As a result, most engineering curricula have introduced a computer programming courses. However, students consider the subject to be unrelated to their core interests and often feel uncomfortable when learning to program for the first time. To overcome these difficulties, several studies have proposed the use of physical computing paradigm. This paradigm takes the computational concepts out of the PC screen and into the real world so that the student can interact with them. This paper proposes Arduino platform as a tool for attracting interest of the programming and reports the results of questionnaire survey analysis.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.132-144
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• 2020

Cloud computing is an emerging technology based on the concept of enabling data access from anywhere, at any time, from any platform. The exponential growth of cloud users has resulted in the emergence of multiple issues, such as the workload imbalance between the virtual machines (VMs) of data centers in a cloud environment greatly impacting its overall performance. Our axis of research is the load balancing of a data center's VMs. It aims at reducing the degree of a load's imbalance between those VMs so that a better resource utilization will be provided, thus ensuring a greater quality of service. Our article focuses on two phases to balance the workload between the VMs. The first step will be the determination of the threshold of each VM before it can be considered overloaded. The second step will be a task allocation to the VMs by relying on an improved and faster version of the meta-heuristic "simulated annealing (SA)". We mainly focused on the acceptance probability of the SA, as, by modifying the content of the acceptance probability, we could ensure that the SA was able to offer a smart task distribution between the VMs in fewer loops than a classical usage of the SA.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.10
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• pp.1237-1247
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• 1999

이질적 분산 환경에서 전자 상거래는 신임장을 기반으로 상거래 참여자들에 대한 인증 서비스가 제공되어야 한다. 본 연구에서는 CORBA 보안 명세 1 를 기반으로 전자 상거래 참여자들에 대한 객체 단위 인증 및 권한 부여 기법을 제공하는 상호 인증 서비스 구조를 제안한다. 이 구조는 Kerberos 2 의 인증 기법 및 인증 키 교환 기법으로 전자 상거래 참여자간에 상대 주체의 신원 확인 뿐 아니라 거래 진행 중 취득한 정보의 근원을 파악할 수 있도록 하였다. 또한 Kerberos 기법을 CORBA 플랫폼 기반의 상호 인증 구조로서 분산 환경에 대해 확장하였으므로 키 관리 등 보안 정보 관리에 있어 효율적이다.Abstract Electronic commerce shall provide its subjects with a credential-based authentication service in the heterogeneous distributed computing environment. In this paper, based on CORBA security service specification 1 which OMG defined, we propose the mutual authentication service for subjects of electronic commerce, providing the authentication of object level and the authenticated key exchange. This proposed structure, by Kerberos 2 for the authentication and the authenticated key exchange, assures not only the identification of a partner but also the confidence of origin of business item for negotiations between subjects of electronic commerce. Since our deployed Kerberos is extended to the mutual authentication service based on CORBA platform, it is efficient for security administration to manage the information such as a key management in the heterogeneous distributed computing environment.

• Korea Information Processing Society Review
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• v.11 no.6
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• pp.56-75
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• 2004

In this article we address some system characteristics and challenging issues in developing Context-aware Middleware for Ubiquitous Computing. The functionalities of a Context-aware Middleware includes gathering context data from hardware/software sensors, reasoning and inferring high-level context data, and disseminating/delivering appropriate context data to interested applications/services. The Middleware should facilitate the query, aggregation, and discovery for the contexts, as well as facilities to specify their privacy policy. Following a formal context model using ontology would enable syntactic and semantic interoperability, and knowledge sharing between different domains. Moddleware should also provide different kinds of context classification mechanical as pluggable modules, including rules written in different types of logic (first order logic, description logic, temporal/spatial logic, fuzzy logic, etc.) as well as machine-learning mechanical (supervised and unsupervised classifiers). Different mechanisms have different power, expressiveness and decidability properties, and system developers can choose the appropriate mechanism that best meets the reasoning requirements of each context. And finally, to promote the context-trigger actions in application level, it is important to provide a uniform and platform-independent interface for applications to express their need for different context data without knowing how that data is acquired. The action could involve adapting to the new environment, notifying the user, communicating with another device to exchange information, or performing any other task.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.103-109
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• 2018

This paper presents an idea and framework to automate a full cycle business process management and re-engineering by integrating traditional business process management systems, process mining, data mining, machine learning, and simulation. We build our framework on the cloud-based platform such that various data sources can be incorporated. We design our systems to be extensible so that not only beneficial for practitioners of BPM, but also for researchers. Our framework can be used as a test bed for researchers without the complication of system integration. The automation of redesigning phase and selecting a baseline process model for deployment are the two main contributions of this study. In the redesigning phase, we deal with both the analysis of the existing process model and what-if analysis on how to improve the process at the same time, Additionally, improving a business process can be applied in a case by case basis that needs a lot of trial and error and huge data. In selecting the baseline process model, we need to compare many probable routes of business execution and calculate the most efficient one in respect to production cost and execution time. We also discuss the challenges and limitation of the framework, including the systems adoptability, technical difficulties and human factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3970-3990
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• 2021

In view of the problems of insufficient data collection and processing capability of multi-source heterogeneous equipment, and low visibility of equipment status at the ship block construction site. A data collection method for ship block construction equipment based on wireless sensor network (WSN) technology and a data processing method based on edge computing were proposed. Based on the Browser/Server (B/S) architecture and the OneNET platform, an online monitoring system for ship block construction equipment was designed and developed, which realized the visual online monitoring and management of the ship block construction equipment status. Not only that, the feasibility and reliability of the monitoring system were verified by using the intelligent tire frame system as the application object. The research of this project can lay the foundation for the ship block construction equipment management and the ship block intelligent construction, and ultimately improve the quality and efficiency of ship block construction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1100-1122
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• 2023

Scheduling user-submitted cloud tasks to the appropriate virtual machine (VM) in cloud computing is critical for cloud providers. However, as the demand for cloud resources from user tasks continues to grow, current evolutionary algorithms (EAs) cannot satisfy the optimal solution of large-scale cloud task scheduling problems. In this paper, we first construct a large- scale multi-objective cloud task problem considering the time and cost functions. Second, a multi-objective optimization algorithm based on multi-factor optimization (MFO) is proposed to solve the established problem. This algorithm solves by decomposing the large-scale optimization problem into multiple optimization subproblems. This reduces the computational burden of the algorithm. Later, the introduction of the MFO strategy provides the algorithm with a parallel evolutionary paradigm for multiple subpopulations of implicit knowledge transfer. Finally, simulation experiments and comparisons are performed on a large-scale task scheduling test set on the CloudSim platform. Experimental results show that our algorithm can obtain the best scheduling solution while maintaining good results of the objective function compared with other optimization algorithms.