• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.547-558
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• 2016

Construction of multi-site Cloud Infrastructure with OpenStack, the most popular cloud open source project with various ICT infrastructure technologies, has operational inefficiency due to installation complexity and geographical limitation. To address this inefficiency, we gradually developed automated installation/configuration tools to automate installation/configuration of Linux and OpenStack by complying with DevOps methodology over a multi-site OpenStack testbed called OF@KOREN SmartX Playground. However, the pre-developed installation tools can be used only for limited cases. Therefore, we designed and developed a prototype of SmartX Provisioning Framework which could conducts Playground-wide provisioning flexibly by following three steps of resource management in Software-defined Infrastructure. We verified the efficiency of the provisioning functionality of the framework by demonstrating an example of automated multi-site cloud construction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.670-679
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• 2012

The recent dissemination of cloud computing makes the amount of data storage to be increased and the cost of storing the data grow rapidly. Accordingly, data and service requests from users also increases the load on the cloud storage. There have been many works that tries to provide low-cost and high-performance schemes on distributed file systems. However, most of them have some weaknesses on performing parallel and random data accesses as well as data accesses of frequent small workloads. Recently, improving the performance of distributed file system based on caching technology is getting much attention. In this paper, we propose a CHPC(Cloud storage High-Performance Caching) framework, providing parallel caching, distributed caching, and proxy caching in distributed file systems. This study compares the proposed framework with existing cloud systems in regard to the reduction of the server's disk I/O, prevention of the server-side bottleneck, deduplication of the page caches in each client, and improvement of overall IOPS. As a results, we show some optimization possibilities on the cloud storage systems based on some evaluations and comparisons with other conventional methods.

• 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.

• Information Systems Review
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• v.17 no.1
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• pp.217-238
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• 2015

Much of the process in Social Science Research can be expedited with use of an automation systems that can lead to research efficiency and dramatic improvement of the research process. This study proposes use of a social science research automation system based on the cloud, which generates questionnaires, supports data collection, and intuitively processes statistical analyses of the data collected. The Cloud-based Social Science Research Automation System is developed with GNU/GPL-based open source software. We also integrate R for statistical computing to enable advanced statistical analyses such as PLS structural equation modeling, mediate effect analysis, compare between groups, and complete general statistics. The Cloud-based Social Science Research Automation system developed in this study is expected to play an important role in improving the social science research process and in performing the social science studies efficiently.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.183-189
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• 2018

With the recent advancement of vehicle wireless communication technology, many vehicular clouds have been proposed. The existing research focused on cloud services through data collection based on vehicular networks of mobile V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure). In this paper, we present a vehicular datacenter model that utilizes the vehicle in the parking space as a resource for the datacenter. Also, we derive resource allocation strategy based on the expected execution time considering the leave rate of each vehicle in our vehicular datacenter model. Simulation results show that our proposed resource allocation strategies outperform the existing strategy in terms of mean execution time.

• Smart Media Journal
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• v.7 no.4
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• pp.9-16
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• 2018

In order to improve the economics and flexibility of cloud computing, tendency to automate the operation and management of cloud resources has become complicated. However, while automation for cloud storage depends on the manufacturer's storage hardware, it cannot flexibly support the storage type in accordance with users' needs. In this paper, we propose an automatic configuration module that supports block/file/object storages suitable for user environment. In order to automatically install ceph, a cloud storage, we propose an automatic installation and configuration module based on the Chef configuration management tool. In addition to that, we also propose an automatic configuration module based on a shell programming in pursuit of enabling users to use ceph storage of block/file/object. The proposed method can automatically set up and manage shared file, block, and object storages in a virtual or physical user environment with no hardware dependencies.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.216-221
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• 2022

The 4th industrial revolution is accelerating the transition to digital innovation in various aspects of our daily lives, and efforts for manufacturing innovation are continuing in the manufacturing industry, such as smart factories. The 4th industrial revolution technology in manufacturing can be used based on AI, big data, IoT, cloud, and robots. Through this, it is required to develop a technology to establish a production facility data collection and analysis system that has evolved from the existing automation and to find the cause of defects and minimize the defect rate. In this paper, we implemented a system that collects power, environment, and status data from production facility sites through IoT devices, quantifies them in real-time in a cloud computing environment, and displays them in the form of MQTT-based real-time infographics using widgets. The real-time sensor data transmitted from the IoT device is stored to the cloud server through a Rest API method. In addition, the administrator could remotely monitor the data on the dashboard and analyze it hourly and daily.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.171-178
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• 2015

In these days, the practical training education is getting highlighted in IT curriculum. This study is for the Cloud computing based Virtual Desktop Service Plan of IT education and its efficient operation and management plan. With the implementation of a virtual lab environment system, the training environment which is customized by the curriculum is able to be provided. Also in the case of the limited system, the curriculum is able to be provided for each subject in advance. Therefore if the Cloud Training (or Practicing) Portal system for the multiple cyber universities is implemented according to this study's estimated scale and operation managing policies, the virtual training education service system could be provided in more efficient and more effective ways.

• Journal of Advanced Navigation Technology
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• v.17 no.2
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• pp.225-233
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• 2013

Recently, Cloud Computing and Big Data has become a buzzword in the field of IT. In this paper, as part of special efforts to support small businesses (SMB) in these situations, we designed the basic prototypes ver. 0.1, 0.2, and 0.5 for Hadoop cluster based on private cloud infrastructure and implemented the part of basic prototypes. And we verified the performances of the basic prototypes using ASA Dataset.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.32-39
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• 2020

In the large-scale infrastructure of cloud environment, illegal access rights are frequently caused by sharing applications and devices, so in order to actively respond to such attacks, a strengthened access control system is required to prepare for each situation. We proposed an entity attribute-based access control(EABAC) model based on security level and relation concept. This model has enhanced access control characteristics that give integrity and confidentiality to subjects and objects, and can provide different services to the same role. It has flexibility in authority management by assigning roles and rights to contexts, which are relations and context related to services. In addition, we have shown application cases of this model in multi service environment such as university.