• Title/Summary/Keyword: 소프트웨어 임대 서비스

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Charge Calculation Scheme for Software Rental Service (소프트웨어 임대 서비스를 위한 사용 요금 계산 기법)

  • Joo, Han-Kyu
    • Journal of Internet Computing and Services
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    • v.9 no.3
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    • pp.119-128
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    • 2008
  • To use commercial software, most software users purchase the software. Some software users, who do not use the software frequently, regard purchasing the software as undue expense. Software rental service can be an effective substitute. To support the software rental service, charging scheme is necessary. Two categories of charging scheme can be considered. One is charging a fixed amount of fee for a fixed period of time and the other is charging a fee based on the actual usage time. In this paper, the software pay-per-use approach based on the amount of time that the software user has used is proposed. The proposed approach gives the capability to calculate the usage time.

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법제코너 / 기업 효율성 높이는 아웃소싱 확산-사용자 보호 위한 법률제정 요구

  • Kim, Yun-Myeong
    • Digital Contents
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    • no.3 s.118
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    • pp.148-155
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    • 2003
  • 새로운 패러다임은 소유에서 접근으로 변모하고 있으며, IT분야에서는 특히 소유보다는 접근과 아웃소싱이라는 새로운경영 패러다임이 형성되고 있다. ASP(Application Service Provider)는 소프트웨어의 구입보다는소프트웨어의 사용권을 취득하고 이를 네트워크를 통해 서비스하는 비지니스 모델이 도입되고 있다. 즉, 일종의 소프트웨어 임대사업이라고 할 수 있는 ASP는 기본적으로 패키지 프로그램을 구입하는 것보다 저렴하게 사용할 수 있는 장점이 있다.

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Implementation of Virtual Machine Allocation Scheme and Lease Service in Cloud Computing Environments (클라우드 컴퓨팅 환경에서 가상머신 할당기법 및 임대 서비스 구현)

  • Hwang, In-Chan;Lee, Bong-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.5
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    • pp.1146-1154
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    • 2010
  • A virtual machine lease service in the cloud computing environment has been implemented using the open source cloud computing platform, OpenNebula. In addition, a web-based cloud user interface is developed for both convenient resource management and efficient service access. The present virtual machine allocation scheme adopted in OpenNebula has performance reduction problem because of not considering CPU allocation scheduler of the virtualization software. In order to address this problem we have considered both the priority of the idle CPU resources of the cluster and credit scheduler of Xen, which resulted in performance improvement of the OpenNebula virtual machine scheduler. The experimental results showed that the proposed allocation scheme provided more virtual machine creations and more CPU resource allocations for cloud service.

A Study on the Utilization of the SaaS Model UPnP Network in e-Trade (전자무역의 SaaS모형 UPnP 네트워크 활용방안에 관한 연구)

  • Jeong, Boon-Do;Yun, Bong-Ju
    • International Commerce and Information Review
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    • v.14 no.4
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    • pp.563-582
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    • 2012
  • In this paper, UPnP Network SaaS model has been studied. Currently, this model of UPnP Network and the trade mission is being used by outsourcing. From now on, the introduction of new trading systems and existing systems and the commercialization of this model as a UPnP network service connection should work. The future of UPnP network SaaS model will become commercially available software, commercial software can be accessed remotely via the Internet should be. Customer site activities must be managed from a central location. Application software architecture, pricing, partnerships, management should not include the character models. N should be the model. When used in small and medium enterprises have a very high value.

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A Study on Realtime Cost Estimation Model of PC Laboratory Service based on Public Cloud (공용 클라우드 기반 PC 실습실 서비스의 실시간 비용 예측 모델 연구)

  • Cho, Kyung-Woon;Shin, Yong-Hyeon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.3
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    • pp.17-23
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    • 2019
  • IaaS is well known as a very cost effective computing service which enables required infrastructures to be rented on demand without ownership of real hardwares. It is very suitable for price sensitive services due to pay-per-use style. Operators of such services would want to adjust utilization policy quickly by estimating costs for cloud infrastructures as soon as possible. However, swift response is not possible due to that cloud service providers provide a dozen or so hours delayed billing information. Our work proposes a realtime IaaS cost estimation model based on usages monitored by virtual machine instance. We operate PC laboratory service on a public cloud during full semester to validate our suggested model. From that experiment, an averaged disparity between estimation and actual cost is less than 5.2%.

Design and Implementation of Library Information System Using Collective Intelligence and Cloud Computing (집단지성과 클라우드 컴퓨팅을 활용한 도서관 정보시스템 설계 및 구현)

  • Min, Byoung-Won
    • The Journal of the Korea Contents Association
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    • v.11 no.11
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    • pp.49-61
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    • 2011
  • In recent, library is considered as an integrated knowledge convergence center that can respond to various requests about information service of users. Therefor it is necessary to establish a novel information system based on information communications technologies of the era. In other words, it is currently required to develop mobile information service available in portable devices such as smart phones or tablet PCs, and to establish information system reflecting cloud computing, SaaS, Annotation, and Library 2.0 etc. In this paper we design and implement a library information system using collective intelligence and cloud computing. This information system can be adapted for the varieties of mobile service paradigm and abruptly increasing amount of electronic materials. Advantages of this concept model are resource sharing, multi-tenant supporting, configuration, and meta-data supporting etc. In addition it can offer software on-demand type user services. In order to test the performance of our system, we perform an effectiveness analysis and TTA authentication test. The average response time corresponding to variance of data reveals 0.692 seconds which is very good performance in timing effectiveness point of view. And we detect maturity level-3 or 4 authentication in TTA tests such as SaaS maturity, performance, and application programs.

A Study on Micro-Mobility Pattern Analysis using Public Bicycle Rental History Data (공공자전거 임대내역 데이터를 활용한 마이크로 모빌리티 패턴분석 연구)

  • Cho, Jaehee;Baik, Gaeun
    • Journal of Information Technology Services
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    • v.20 no.6
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    • pp.83-95
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    • 2021
  • In this study, various usage patterns were analyzed after establishing a data mart for micro mobility analysis based on the rental history of public bicycles in Seoul. Rental history data is origin-destination data that includes the rental location and time, and the return location and time. About 1500 rental locations were classified according to the characteristics of the location to create a 'station type' dimension. We also created a 'path type' dimension that displays whether the rental location and return location are the same. In addition, a derived variable called speed, which is obtained by dividing the distance used by the time used, is added, and through this, the characteristics of the riding area and the reason for the rental can be estimated. Meanwhile, administrative district link, administrative neighborhood link, and station type link were created to apply network analysis. Through this analysis, the roles and proportions of administrative districts, public facilities, and private facilities engaged in micro-mobility services were visualized. 49.9% of rentals occur at rental offices near transportation facilities, and half of them occur at rental offices near subway stations. The number of rentals during the evening rush hour is more than double that of the morning rush hour. When the path type is unidirectional, there is a fixed destination, so the distance and time used are short, and the movement speed tends to be high. In the case of round-trip, the purpose of use is exercise or leisure, so the distance and time used are long, and the movement speed is slow. It is expected that the results of the analysis can be used as reference materials for selecting new rental locations, providing convenient services for users, and developing user-specialized products.

Economic Impact of HEMOS-Cloud Services for M&S Support (M&S 지원을 위한 HEMOS-Cloud 서비스의 경제적 효과)

  • Jung, Dae Yong;Seo, Dong Woo;Hwang, Jae Soon;Park, Sung Uk;Kim, Myung Il
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.10
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    • pp.261-268
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    • 2021
  • Cloud computing is a computing paradigm in which users can utilize computing resources in a pay-as-you-go manner. In a cloud system, resources can be dynamically scaled up and down to the user's on-demand so that the total cost of ownership can be reduced. The Modeling and Simulation (M&S) technology is a renowned simulation-based method to obtain engineering analysis and results through CAE software without actual experimental action. In general, M&S technology is utilized in Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Multibody dynamics (MBD), and optimization fields. The work procedure through M&S is divided into pre-processing, analysis, and post-processing steps. The pre/post-processing are GPU-intensive job that consists of 3D modeling jobs via CAE software, whereas analysis is CPU or GPU intensive. Because a general-purpose desktop needs plenty of time to analyze complicated 3D models, CAE software requires a high-end CPU and GPU-based workstation that can work fluently. In other words, for executing M&S, it is absolutely required to utilize high-performance computing resources. To mitigate the cost issue from equipping such tremendous computing resources, we propose HEMOS-Cloud service, an integrated cloud and cluster computing environment. The HEMOS-Cloud service provides CAE software and computing resources to users who want to experience M&S in business sectors or academics. In this paper, the economic ripple effect of HEMOS-Cloud service was analyzed by using industry-related analysis. The estimated results of using the experts-guided coefficients are the production inducement effect of KRW 7.4 billion, the value-added effect of KRW 4.1 billion, and the employment-inducing effect of 50 persons per KRW 1 billion.