• Title/Summary/Keyword: Enterprise Cloud Computing

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The SWOT-AHP Framework for the Enterprise Cloud Computing Strategy (기업의 클라우드 컴퓨팅 전략수립을 위한 SWOT-AHP 프레임워크 개발)

  • Tang, Nguyen Hanh;Shao, Jing;Lee, Young-Chan
    • The Journal of Information Systems
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    • v.22 no.2
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    • pp.85-104
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    • 2013
  • 최근 클라우드 컴퓨팅이 학계나 실무계에서 많은 주목을 받고 있으며, 공공기관에서도 클라우드 컴퓨팅을 도입하고 있는 추세에 있다. 클라우드 컴퓨팅은 장 단점을 모두 가지고 있지만 지속적으로 발전하고 있으며, 기업들은 클라우드 기반의 정보시스템을 도입하기 위한 다양한 솔루션들을 활용하고 있다. 따라서 기업에서 클라우드 컴퓨팅 도입을 위해 고려해야 할 요소들은 무엇이며, 어떻게 계획을 수립할 것인지는 시급한 과제라고 할 수 있다. 본 논문의 목적은 기업이 클라우드 컴퓨팅 채택 전략을 수립하기 위한 프레임 워크를 제시하는 것이다. 구체적으로, SWOT-AHP는 클라우드 컴퓨팅을 실행하는 과정에서 강점-약점-기회-위협 요인을 파악하고, 전략 계획을 보다 효율적으로 수립 하는데 사용된다. 경영전략 이론에서 널리 알려져 있는 SWOT과 다기준의사결정기법 중 실무에서 가장 활발하게 사용되고 있는 AHP는 복잡하지 않고 적용이 쉽기 때문에 본 연구에서 제안하는 방법을 이용한다면 실무에서도 큰 어려움 없이 SWOT-AHP 프레임워크를 클라우드 컴퓨팅 전략수립에 적용할 수 있을 것으로 기대한다.

A Study on the Architecture of Cloud Hospital Information System for Small and Medium Sized Hospitals (중소형 병원의 클라우드 병원정보시스템 서비스 체계에 관한 연구)

  • Lee, Nan Kyung;Lee, Jong Ok
    • The Journal of Society for e-Business Studies
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    • v.20 no.3
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    • pp.89-112
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    • 2015
  • Recently, the business environment of healthcare has changed rapidly due to the entering the mobile era, the intensifying global competition, and the explosion of healthcare needs. Despite of necessity in expanding new IT-based medical services and investing IT resources to respond environmental changes, the small and medium sized hospitals could not realize these requirements due to the limited management resources. CHISSMH is designed and presented in this research to provide high valued clouding medical services with reasonable price. CHISMH is designed and presented in this research to provide high valued medical services with reasonable price through cloud computing. CHISME is designed to maximize resource pooling and sharing through the visualization. By doing so, Cloud Service provider could minimize maintenance cost of cloud data center, provide high level services with reasonable pay-per-use price. By doing so, Cloud Service provider could minimize maintenance cost of cloud data center, and could provide high level services with reasonable pay-per-use price. CHISME is expected to be base framework of cloud HIS services and be diffusion factor of cloud HIS services Operational experience in CHISSMH with 15 hospitals is analyzed and presented as well.

Modeling of Virtual Switch in Cloud System (클라우드 시스템의 가상 스위치 모델링)

  • Ro, Cheul-Woo
    • Journal of Digital Convergence
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    • v.11 no.12
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    • pp.479-485
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    • 2013
  • Virtualization is a promising approach to consolidating multiple online services onto a smaller number of computing resources. A virtualized server environment allows computing resources to be shared among multiple performance isolated platforms called virtual machines. Through server virtualization software, applications servers are encapsulated into VMs, and deployed with APIs on top generalized pools of CPU and memory resources. Networking and security have been moved to a software abstraction layer that transformed computing, network virtualization. And it paves the way for enterprise to rapidly deploy networking and security for any application by creating the virtual network. Stochastic reward net (SRN) is an extension of stochastic Petri nets which provides compact modeling facilities for system analysis. In this paper, we develop SRN model of network virtualization based on virtual switch. Measures of interest such as switching delay and throughput are considered. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results are obtained according to the virtual switch capacity and number of active VMs.

Performance Evaluation and Optimization of NoSQL Databases with High-Performance Flash SSDs (고성능 플래시 SSD 환경에서 NoSQL 데이터베이스의 성능 평가 및 최적화)

  • Han, Hyuck
    • The Journal of the Korea Contents Association
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    • v.17 no.7
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    • pp.93-100
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    • 2017
  • Recently, demands for high-performance flash-based storage devices (i.e., flash SSD) have rapidly grown in social network services, cloud computing, super-computing, and enterprise storage systems. The industry and academic communities made the NVMe specification for high-performance storage devices, and NVMe-based flash SSDs can be now obtained in the market. In this article, we evaluate performance of NoSQL databases that social network services and cloud computing services heavily adopt by using NVMe-based flash SSDs. To this end, we use NVMe SSD that Samsung Electronics recently developed, and the SSD used in this study has performance up to 3.5GB/s for sequential read/write operations. We use WiredTiger for NoSQL databases, and it is a default storage engine for MongoDB. Our experimental results show that log processing in NoSQL databases is a major overhead when high-performance NVMe-based flash SSDs are used. Furthermore, we optimize components of log processing and optimized WiredTiger show up to 15 times better performance than original WiredTiger.

Data Cleaning System using XMDR-DAI in Cloud (클라우드 환경에서 XMDR-DAI를 이용한 데이터 정제 시스템)

  • Moon, Seok-Jae;Jeong, Kye-Dong;Lee, Jong-Yong;Cho, Young-Keun
    • Journal of Digital Convergence
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    • v.12 no.2
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    • pp.263-270
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    • 2014
  • In cloud environment, business intelligence data warehouse is used for decision making and enterprise policy. But if new system is added in cloud environment, much cost and time is needed due to heterogenous characteristics in data integration. This paper suggests a data cleaning system for business intelligence in cloud environment. The proposed system minimizes the effect of local system when it integrates distributed system using XMDR-DAI. And this system provides standardized information to generate information of data warehouse in real time. Also the proposed system saves cost and time by integrating the data without a change of existed system. And it can improve quality of information by generating coherent information through data extraction and cleaning work in real time.

The Study of the SOA Enabled ERP Systems Implementation in Service Industry: Case Study

  • Kim, Gyu-C.
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.1
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    • pp.73-93
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    • 2012
  • The primary objective of this research is to explain how to implement the Service Oriented Architecture (hereafter SOA) enabled Enterprise Resource Planning (hereafter ERP) system successfully for service industries. An implementation of the ERP system help many organizations to alleviate the difficult job of supporting inflexible or legacy systems that in most cases result in cost increases, data redundancy and inaccuracy, and various inefficiencies. However, the ERP system is losing its market share rapidly to the cloud computing system which utilizes the Software-as-a-service (hereafter SaaS) and SOA. The SOA is an approach to integrate various types of IT resources to leverage existing ERP system, while at the same time building an infrastructure that can readily respond to new business environment and offer new dynamic applications. The companies that implement this system have less of a need for the kinds of all-in-one ERP system that have dominated the back office for decades and can move freely to best-of-breed applications. This research will identify the benefits and costs of the SOA enabled ERP system through case studies and its impact on competitive priorities such as cost, quality, delivery, and flexibility.

A Study on User Authentication Method for Using Cloud Computing in an Enterprise (기업에서 클라우드 컴퓨팅 사용을 위한 사용자 인증기법 연구)

  • Kimo, Young-Gon;Kim, Hyo-Jong;Jun, Moon-Seog
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06d
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    • pp.42-46
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    • 2010
  • 최근 새로운 트렌드를 형성하고 있는 클라우드 컴퓨팅은 인터넷 기술을 활용하여 다수의 사용자들에게 IT 자원을 서비스하는 시스템이다. 이러한 서비스들이 많이 나타나고 있지만 아직은 많은 보안 문제점이 있다. 기업의 입장에서는 기업 정보나 고객 정보 등의 유출 및 훼 손에 대한 보안문제로 클라우드 컴퓨팅을 기피하는 사례도 발생한다. 따라서 본 논문에서는 기업에서 클라우드 컴퓨팅 사용을 위한 기본적인 사용자 인증은 클라우드 컴퓨팅을 제공하는 업체에서 하며, 보안과 접근통제가 필요한 서비스에 대해서는 기업 자체에서 인증을 한다. 즉, 온전한 클라우드 컴퓨팅 서비스를 받기 위해서 총 2 번의 인증을 거쳐 필요한 서비스에 접근이 가능하도록 하는 안전하고 정확한 인증기법을 제안하였다.

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Behavioral Analysis Zero-Trust Architecture Relying on Adaptive Multifactor and Threat Determination

  • Chit-Jie Chew;Po-Yao Wang;Jung-San Lee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.9
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    • pp.2529-2549
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    • 2023
  • For effectively lowering down the risk of cyber threating, the zero-trust architecture (ZTA) has been gradually deployed to the fields of smart city, Internet of Things, and cloud computing. The main concept of ZTA is to maintain a distrustful attitude towards all devices, identities, and communication requests, which only offering the minimum access and validity. Unfortunately, adopting the most secure and complex multifactor authentication has brought enterprise and employee a troublesome and unfriendly burden. Thus, authors aim to incorporate machine learning technology to build an employee behavior analysis ZTA. The new framework is characterized by the ability of adjusting the difficulty of identity verification through the user behavioral patterns and the risk degree of the resource. In particular, three key factors, including one-time password, face feature, and authorization code, have been applied to design the adaptive multifactor continuous authentication system. Simulations have demonstrated that the new work can eliminate the necessity of maintaining a heavy authentication and ensure an employee-friendly experience.

An Analysis of Utilization on Virtualized Computing Resource for Hadoop and HBase based Big Data Processing Applications (Hadoop과 HBase 기반의 빅 데이터 처리 응용을 위한 가상 컴퓨팅 자원 이용률 분석)

  • Cho, Nayun;Ku, Mino;Kim, Baul;Xuhua, Rui;Min, Dugki
    • Journal of Information Technology and Architecture
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    • v.11 no.4
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    • pp.449-462
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    • 2014
  • In big data era, there are a number of considerable parts in processing systems for capturing, storing, and analyzing stored or streaming data. Unlike traditional data handling systems, a big data processing system needs to concern the characteristics (format, velocity, and volume) of being handled data in the system. In this situation, virtualized computing platform is an emerging platform for handling big data effectively, since virtualization technology enables to manage computing resources dynamically and elastically with minimum efforts. In this paper, we analyze resource utilization of virtualized computing resources to discover suitable deployment models in Apache Hadoop and HBase-based big data processing environment. Consequently, Task Tracker service shows high CPU utilization and high Disk I/O overhead during MapReduce phases. Moreover, HRegion service indicates high network resource consumption for transfer the traffic data from DataNode to Task Tracker. DataNode shows high memory resource utilization and Disk I/O overhead for reading stored data.

A Container Orchestration System for Process Workloads

  • Jong-Sub Lee;Seok-Jae Moon
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.270-278
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    • 2023
  • We propose a container orchestration system for process workloads that combines the potential of big data and machine learning technologies to integrate enterprise process-centric workloads. This proposed system analyzes big data generated from industrial automation to identify hidden patterns and build a machine learning prediction model. For each machine learning case, training data is loaded into a data store and preprocessed for model training. In the next step, you can use the training data to select and apply an appropriate model. Then evaluate the model using the following test data: This step is called model construction and can be performed in a deployment framework. Additionally, a visual hierarchy is constructed to display prediction results and facilitate big data analysis. In order to implement parallel computing of PCA in the proposed system, several virtual systems were implemented to build the cluster required for the big data cluster. The implementation for evaluation and analysis built the necessary clusters by creating multiple virtual machines in a big data cluster to implement parallel computation of PCA. The proposed system is modeled as layers of individual components that can be connected together. The advantage of a system is that components can be added, replaced, or reused without affecting the rest of the system.