• The KIPS Transactions:PartA
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• v.13A no.2 s.99
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• pp.157-162
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• 2006

Recent High Performance Computing (HPC) platforms can be classified as Shared-Memory Multiprocessors (SMP), Massively Parallel Processors (MPP), and Clusters of computing nodes. These platforms are deployed in many scientific and engineering applications which require very high demand on computing power. In order to realize an optimal performance for these applications, it is crucial to find and use the suitable computing platforms and programming paradigms. In this paper, we use SPEC HPC 2002 benchmark suite developed in various parallel programming models (MPI, OpenMP, and hybrid of MPI/OpenMP) to find an optimal computing environments and programming paradigms for them through their performance analyses.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.440-444
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• 2018

Purpose: Cloud-computing technology has several advantages, including maintenance, management, accessibility, and computing power. A greenhouse-control system utilizing these advantages was developed using a private cloud-computing system. Methods: A private cloud needs a collection of servers and a suite of software tools to monitor and control cloud-computing resources. In this study, a server farm, operated by OpenStack as a cloud platform, was constructed using servers, and other network devices. Results: The greenhouse-control system was developed according to the fundamental cloud service models: infrastructure as a service, platform as a service, and software as a service. This system has four additional advantages - security, control function, public data use, and data exchange. There are several considerations that must be addressed, such as service level agreement, data ownership, security, and the differences between users. Conclusions: When the advantages are utilized and the considerations are addressed, cloud-computing technology will be beneficial for agricultural use.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.254-255
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• 2007

유비쿼터스 컴퓨팅의 핵심 구성요소인 웨어러블 컴퓨터는 배터리를 기반으로 운영되므로 웨어러블 컴퓨터의 사용 시간을 늘리려면 효과적인 전력관리가 필요하다. 본 논문에서는 웨어러블 컴퓨터의 전력관리를 위한 컴포넌트 형태 미들웨어에 대한 구현 상황과 그 성능에 대해 기술한다. 구현된 전력관리 미들웨어는 전력인지 인터페이스, 전력관리 모듈과 전력관리 미들웨어 인터페이스로 구성된다. 구현된 전력인지 인터페이스로 전력관리 미들웨어 인터페이스는 다른 미들웨어 컴포넌트 개발자나 응용프로그램 개발자에게 시스템에 투명한 전력관리 기법을 제공할 수 있다. 성능 측정 결과, 구현된 전력관리 미들웨어를 이용하여 LCD 화면 밝기와 블루투스 장치 검색 메시지 주기를 조절할 경우, 웨어러블 컴퓨터의 이용시간이 약 2배 이상 증가하였다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.302-303
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• 2015

이 논문은 빅데이터 활용을 위한 Cloud computing 기반 전력 시스템 해석을 위한 조류계산 알고리즘을 개발하고자 한다. 하지만 컴퓨터 연산 속도의 빠른 발전으로 이미 기존 조류계산 알고리즘을 이용하여 전력 시스템을 해석하는데 많은 시간이 소요되지 않는다. 그럼에도 불구하고 우리는 계통이 안전하게 운영될 수 있도록 하기 위해 다양한 상정고장을 고려하여 계통 해석을 해야 하며 또한 해석 결과와 그 원인과의 상관관계를 분석하기에는 많은 어려움이 있는 실정이다. 이에 본 논문에서는 Cloud computing을 이용하여 빅데이터 기반 조류계산 알고리즘을 구현하고자 한다. 본 논문에서 제안하는 빅데이터 기반 조류게산 알고리즘 기반 계통 해석시 중간에 파생되는 결과나 최종 결과 등의 분석을 통해 보다 효율적이고 안정한 계통 운영에 기여할 수 있을 것이다.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2222-2232
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• 1999

This paper proposed a Systolic Arrays architecture for computing edge detection on images. It is very difficult to be processed images to real time because of operations of local operators. Local operators for computing edge detection are to be used in many image processing tasks, involve replacing each pixel in an image with a value computed within a local neighborhood of that pixel. Computing such operators at the video rate requires a computing power which is not provided by conventional computer. Through computationally expensive, it is highly regular. Thus, this paper presents a systolic arrays for tasks such as edge detection and laplacian, which are defined in terms of local operators.

• Journal of information and communication convergence engineering
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• v.13 no.1
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• pp.15-20
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• 2015

The limited battery power in the mobile environment, lack of sufficient wireless bandwidth, limited resources of mobile terminals, and frequent breakdowns of the wireless network have become major hurdles in the development of mobile cloud computing (MCC). In order to solve the abovementioned problems, This paper propose a proxy-based MCC framework by adding a proxy server between mobile devices and cloud services to optimize the access to cloud services by mobile devices on the network transmission, application support, and service mode levels. Finally, we verify the effectiveness of the developed framework through an experimental analysis. This framework can ensure that mobile users have efficient access to cloud services.

• ETRI Journal
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• v.40 no.1
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• pp.61-71
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• 2018

In this study, we developed hybrid control algorithms in smart base stations (SBSs) along with devised communication, caching, and computing techniques. In the proposed scheme, SBSs are equipped with computing power and data storage to collectively offload the computation from mobile user equipment and to cache the data from clouds. To combine in a refined manner the communication, caching, and computing algorithms, game theory is adopted to characterize competitive and cooperative interactions. The main contribution of our proposed scheme is to illuminate the ultimate synergy behind a fully integrated approach, while providing excellent adaptability and flexibility to satisfy the different performance requirements. Simulation results demonstrate that the proposed approach can outperform existing schemes by approximately 5% to 15% in terms of bandwidth utilization, access delay, and system throughput.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.95-100
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• 2022

Cloud computing platform is a shared pool of resources and services with various kind of models delivered to the customers through the Internet. The methods include an on-demand dynamically-scalable form charged using a pay-per-use model. The main problem with this model is the allocation of resource in dynamic. In this paper, we have proposed a mechanism to optimize the resource provisioning task by reducing the job completion time while, minimizing the associated cost. We present the Cooperative Agents Dynamic Resource Allocation and Monitoring in Cloud Computing CADRAM system, which includes more than one agent in order to manage and observe resource provided by the service provider while considering the Clients' quality of service (QoS) requirements as defined in the service-level agreement (SLA). Moreover, CADRAM contains a new Virtual Machine (VM) selection algorithm called the Node Failure Discovery (NFD) algorithm. The performance of the CADRAM system is evaluated using the CloudSim tool. The results illustrated that CADRAM system increases resource utilization and decreases power consumption while avoiding SLA violations.

• Advances in nano research
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• v.15 no.6
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• pp.513-520
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• 2023

The exponential proliferation of cutting-edge computing technologies has spurred organizations to outsource their data and computational needs. In the realm of cloud-based computing environments, ensuring robust security, encompassing principles such as confidentiality, availability, and integrity, stands as an overarching imperative. Elevating security measures beyond conventional strategies hinges on a profound comprehension of malware's multifaceted behavioral landscape. This paper presents an innovative paradigm aimed at empowering cloud service providers to adeptly model user behaviors. Our approach harnesses the power of a Particle Swarm Optimization-based Probabilistic Neural Network (PSO-PNN) for detection and recognition processes. Within the initial recognition module, user behaviors are translated into a comprehensible format, and the identification of malicious nano-structures behaviors is orchestrated through a multi-layer neural network. Leveraging the UNSW-NB15 dataset, we meticulously validate our approach, effectively characterizing diverse manifestations of malicious nano-structures behaviors exhibited by users. The experimental results unequivocally underscore the promise of our method in fortifying security monitoring and the discernment of malicious nano-structures behaviors.

• The Journal of Korean Association of Computer Education
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• v.13 no.1
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• pp.53-64
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• 2010

In this paper, we tried to enable a mobile device as a resource to access to mobile grid networks. By advanced Internet techniques, the use of mobile devices has been rapidly increased. Some researches in mobile grid computing tried to combine grid computing with mobile devices. However, according to intrinsic properties of mobile environments, mobile devices have many considerations, such as mobility management, disconnected operation, device heterogeneity, service discovery, resource sharing, security, and so on. To solve these problems, there are two trends for mobile grid computing: a proxy-based mobile grid architecture and an agent-based mobile grid architecture. We focus on a proxy-based mobile grid architecture with IP-paging, which can easily manage idle mobile devices and grid resource status information. Also, we use SIP(Session Initiation Protocol)to support mobility management, mobile grid services. We manage variation of mobile device state and power by paging cache. Finally, using the candidate set and the reservation set of resources, we perform task migration. The performance evaluation by simulation, shows improvement of efficiency and stability during execution.