정보제어넷 기반 클라우드 워크플로우 모델

순카이 ( Kai Sun ),안현 ( Hyun Ahn ),김광훈 ( Kwanghoon Pio Kim ) 한국인터넷정보학회 2018 인터넷정보학회논문지 Vol.19 No.3

본 논문에서는 클라우드 컴퓨팅 환경을 기반으로 하는 실시간 엔터프라이즈 워크플로우 관리 시스템을 구현하는데 있어서 반드시 수반되어야 하는 워크플로우 모델링 방법론으로서 정보제어넷 기반 클라우드 워크플로우 모델을 제안한다. 본 논문에서 제안하는 모델은 클라우드 서비스 배치모델을 기반으로 하는 클라우드 워크플로우 아키텍처, 즉 조직 수준 클라우드 배치모델, 커뮤니티 수준 클라우드 배치모델, 공적 수준 클라우드 배치모델, 혼합형 클라우드 배치모델 등으로 분류되는 클라우드 배치모델에 따른 클라우드 워크플로우 아키텍처를 지원하는 것을 목적으로 한다. 이 모델은 전통적으로 엔터프라이즈 워크플로우의 대표적인 정형적 모델링 기법인 정보제어넷 모델링 방법론을 클라우드 배치모델과 연계할 수 있도록 확장시킨 수학적 그래프 모델이다. 결론적으로, 본 논문에서는 제안된 정보제어넷 기반 클라우드 워크플로우 모델을 적용할 수 있는 클라우드 워크플로우 아키텍처와 그에 따른 클라우드 워크플로우 서비스를 설계함으로써 제안된 모델의 적용가능성을 검증한다. This paper proposes a cloud workflow model theoretically supported by the information control net modeling methodology as a cloud workflow modeling methodology that is mandatory in implementing realtime enterprise workflow management systems running with cloud computing environments. The eventual goal of the cloud workflow model proposed in this paper is to support those cloud workflow architectures reflecting the types of cloud deployment models such as private, community, public, and hybrid cloud deployment models. Moreover, the proposed model is a mathematical graph model that is extended from the information control net modeling methodology used in conventional enterprise workflow modeling, and it aims to theoretically couple this methodology with the cloud deployment models. Finally, this paper tries to verify the feasibility of the proposed model by building a possible cloud workflow architecture and its cloud workflow services on a realtime enterpeise cloud workflow management system.

The Recognition Method of Radiation Source Based on Information Entropy and Cloud Model

Yun Lin,Can Wang,Chunguang Ma,Zheng Dou,Zhiqiang Wu,Zhiping Zhang 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.2

Information entropy features are often used for radiation source signal recognition, but due to the information entropy is very sensitive to noise, so this method has greater recognition rate changes with the SNR. This paper putting forward a viable recognition based on Entropy and cloud model. using cloud model to extract secondary features of signals, build radiation source signal’s entropy and cloud feature vector. The method uses cloud model description and processing interval fuzzy and observation noise data, better solve the low SNR cases of radiation source signal feature extraction problem. At the same time, putting forward the similar cloud classification recognition algorithm based on cloud model. The simulation results show that Entropy and cloud model has better recognition effect under low SNR, which can improve the signals’ recognition rate under low SNR.

파이프 라인 리트로피팅 어플리케이션을 위한 3D 포인트 클라우드, CAD 모델, 실시간 카메라 뷰 및 부분 포인트 클라우드의 4 대 1 정렬

안도윤(Do Yoon Ahn),아제이 쿠말(G Ajay Kumar),아쇽 쿠말 파틸(Ashok Kumar Patil),채영호(Young Ho Chai) 대한기계학회 2018 大韓機械學會論文集A Vol.42 No.8

레이저 스캐닝된 3D 포인트 클라우드 데이터 및 CAD(Computer Aided Design)모델을 이용하면 중화학플랜트에서의 복잡한 공학적 모델의 건설, 모니터링 및 리트로피팅에 큰 이점이 있다. 또한, BIM(Building Information Modeling) 프로세스에 필요한 시간, 노력 및 비용을 절감할 수 있다. 레이저 스캐닝으로 생성 된 포인트 클라우드 데이터와 실제 모델을 매칭시켜 보면 사용자가 실제 모델에 해당하는 부분의 특정 요소를 찾아 분석하고 수정하는 것이 용이하다. 본 논문은 포인트 클라우드의 획득, 생성된 포인트 클라우드 데이터와 물리적 모델의 정렬, 적응형 3D 모델링을 포함한 리트로피팅을 위한 프레임워크를 제시한다. 워크플로우는 효율적인 4 in 1 접근 방식으로, 첫번째로 LiDAR(Light Detection And Ranging)의 실시간 부분 포인트 클라우드를 사용하여 실제 물리적 모델과 사전에 수집, 재구성한 포인트 클라우드 데이터와 정렬하고, 그 후 정렬된 포인트 클라우드 데이터를 사용하여 3D모델의 자동생성 및 생성된 CAD의 가상 리트로피팅을 수행한다. 마지막으로 VR(Virtual Reality)기기를 이용하여 생성된 3D모델을 실제 카메라 뷰에 중첩하여 보여줌으로써 효율적으로 시각화를 완성한다. 이 방법은 LiDAR에서 얻어지는 부분 포인트 클라우드 데이터와 사전에 수집, 재구성한 포인트 클라우드 데이터 및 플랜트 CAD 모델을 사용하여 실제환경에서 시연되었다. The use of laser scanned 3D point cloud data and computer aided design (CAD) models aids in the construction, monitoring, and retrofitting of complex engineering objects in petrochemical plants. Moreover, it reduces the time, effort, and cost required for the building information modeling (BIM) process. Connecting the laser scanner generated point cloud data with the physical world enables users to find, analyze, and modify the specific element of the model corresponding to the physical model. This paper presents a framework for point cloud acquisition, alignment of generated point cloud data with the physical world model, adaptive 3D modeling, and retrofitting. The workflow includes an efficient 4-in-1 approach, beginning with the alignment of pre-processed point cloud data with the realworld physical model using a real-time partial point cloud obtained from light detection and ranging (LiDAR), followed by the automation of 3D model generation from the point cloud data and virtual retrofitting of CAD models. Finally, an overlap of the generated 3D models on the real environment from the camera view is efficiently visualized using a wearable virtual reality (VR) device. The proposed method is demonstrated in a real-world setting, using the partial point cloud from LiDAR, pre-processed real-world point cloud data, and CAD models of an industrial plant.

Reference Architecture and Operation Model for PPP (Public-Private-Partnership) Cloud

( Youngkon Lee ),( Ukhyun Lee ) 한국정보처리학회 2021 Journal of information processing systems Vol.17 No.2

The cloud has already become the core infrastructure of information systems, and government institutions are rapidly migrating information systems to the cloud. Government institutions in several countries use private clouds in their closed networks. However, because of the advantages of public clouds over private clouds, the demand for public clouds is increasing, and government institutions are expected to gradually switch to public clouds. When all data from government institutions are managed in the public cloud, the biggest concern for government institutions is the leakage of confidential data. The public-private-partnership (PPP) cloud provides a solution to this problem. PPP cloud is a form participation in a public cloud infrastructure and the building of a closed network data center. The PPP cloud prevents confidential data leakage and leverages the benefits of the public cloud to build a cloud quickly and easily maintain the cloud. In this paper, based on the case of the PPP cloud applied to the Korean government, the concept, architecture, operation model, and contract method of the PPP cloud are presented.

휘처 기반 클라우드 모델링 방법

송치양,조은숙 한국지식정보기술학회 2022 한국지식정보기술학회 논문지 Vol.17 No.1

The IT paradigm has evolved from web computing to cloud computing environment. Cloud service development has been mainly studied by object-oriented design method based on UML, but research by feature design method is weak. In order to improve the usability and reusability of feature-oriented cloud modeling, this paper proposes a meta-model-based feature cloud modeling method suitable for the characteristics of cloud computing services. To do this, the MDA-based hierarchical cloud-feature integration metamodel is established for how the elements of the cloud characteristics are expressed in the modeling elements of the feature. In terms of applying this integrated metamodel, we make a feature-oriented cloud modeling process from the requirements definition (CIM) phase to the analysis (PIM) and design (PSM) phase for cloud application development. The work activity in the development phase is defined to create a model by using the modeling elements and relationships of the formalized integrated meta-model. In terms of applying this process, case study is shown with the PDMCS system. This facilitates the design of a hierarchical cloud application using the feature cloud modeling method. In addition, by using a standardized feature-based meta-model and modeling process, it is possible to design a cloud service model that is easier and more clear. Moreover, the creation of a reusable cloud application model for each development stage by the MDA way can be further improved.

Cost model based service placement in federated hybrid clouds

Altmann, J.,Kashef, M.M. North-Holland 2014 Future generations computer systems Vol.41 No.-

As cloud federation allows companies in need of computational resources to use computational resources hosted by different cloud providers, it reduces the cost of IT infrastructure by lowering capital and operational expenses. This is the result of economies of scale and the possibility for organizations to purchase just as much computing and storage resources as needed whenever needed. However, a clear specification of cost savings requires a detailed specification of the costs incurred. Although there are some efforts to define cost models for clouds, the need for a comprehensive cost model, which covers all cost factors and types of clouds, is undeniable. In this paper, we cover this gap by suggesting a cost model for the most general form of a cloud, namely federated hybrid clouds. This type of cloud is composed of a private cloud and a number of interoperable public clouds. The proposed cost model is applied within a cost minimization algorithm for making service placement decisions in clouds. We demonstrate the workings of our cost model and service placement algorithm within a specific cloud scenario. Our results show that the service placement algorithm with the cost model minimizes the spending for computational services.

A New Conceptual Framework Modelling for Cloud Computing Risk Management in Banking Organizations

Abdelrafe Elzamly,Burairah Hussin,Samy Abu Naser,Khalid Khanfar,Mohamed Doheir,Ali Selamat,Abdullah Rashed 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.9

Despite much research and progress in the areas of cloud computing project, many cloud computing projects have a very high failure rate when it comes to the banking organizations. The aim of this study is to propose a new conceptual framework modelling for cloud computing risk management in banking organizations. There are the main five stages for a successful cloud computing framework in a banking organization as described in Figure 1: Cloud mobility and cloud banking applications, cloud service models, cloud deployment models, cloud risk management models, and cloud security models. As a future work, we will apply the framework in the real banking world to mitigate and control the security issues. A successful framework modelling for cloud computing risk management will greatly improve the probability of cloud computing success in banking organizations.

Cloud-Based Accounting Adoption in Jordanian Financial Sector

ELDALABEEH, Abdel Rahman,AL-SHBAIL, Mohannad Obeid,ALMUIET, Mohammad Zayed,BANY BAKER, Mohammad,E'LEIMAT, Dheifallah Korea Distribution Science Association 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.2

Cloud accounting represents a new area of accounting information systems. Past research has often focused on accounting information systems and its antecedents, rather than factors that adopt cloud accounting system. The purpose of this paper is to explain the factors that influence the adoption of cloud accounting in the financial sectors. This paper applied the technology acceptance model (TAM), technology-organization-environment, and the De Lone and Mc Lean model, coupled with proposed factors relevant to cloud accounting. The proposed model was empirically evaluated using survey data from 187 managers (financial managers, IT department managers, audit managers, heads of accounting departments, and head of internal control departments) in Jordanian bank branches. Based on the SEM results, top management support, organizational competency, service quality, system quality, perceived usefulness, and perceived ease of use had a positive relationship with the intention of using cloud accounting. Cloud accounting adoption positively affected cloud accounting usage. This paper contributes to a theoretical understanding of factors that activate the adoption of cloud accounting. For financial firms in general the results enable them to better develop cloud accounting framework. The paper verifies the factors that affect the adoption of cloud accounting and the proposed cloud accounting model.

An exploratory study on price model of cloud service in public sector

Jonghei Ra,Seojun Lee,Youngjin Choi 한국EA학회 2018 한국EA학회 학술발표논문집 Vol.2018 No.12

The government is expected to accelerate the adoption of cloud computing in the public sector with the enactment of the Law on the Development of Cloud Computing and Protection of Users. However, in order to estimate the cost of introducing cloud computing in the public sector, there is no adequate calculation model. In most cases, the IT manager admits the cloud computing cost presented by the developer. This makes it difficult to judge the appropriateness or cost of public cloud computing. Therefore, this study intends to develop an accurate and easy-to-use model that is suitable for domestic situation and applicable to cloud computing business.

A Study on Big Data Reliable Combination Evaluation Method based on the Cloud Service Qos Model

Li Xiating,Song Rong 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.12

The vigorous development of various technologies in the cloud computation field promotes the development and progress of cloud services. But with the large accumulation of information data in the cloud services, in order to meet user’s needs of cloud services multi-function, the operation capacity of a single cloud service is not enough. Now, combining two or many cloud services is a hot research problem. The other hot research problem is that the task of data construction is assigned to different cloud service platforms. However, the combination schemes are too much, so how to ensure the optimal scheme is credible? It has become the key to solve the problem. After reading a large number of literatures, the paper proposes the big data reliable combination evaluation method based on the cloud service QoS model. By getting the contribution of each of the services in the combination scheme set, the method chooses the optimal cloud service combination scheme. Then the optimal scheme is evaluated its reliability.