• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.25-32
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• 2018

In this paper, we present a proposed monitoring system for smart factories with several aspects, including information gathering, analysis, control, and display that relate to concurrently operation processes in the factory area. This paper proposes a monitoring and management system for industrial automation. In particular, it uses an Internet of Thing (IoT) device with a data protocol unit to convert the industrial protocols and transfer the information on various parameters. In the case of data communication, the proposed monitoring system is designed to support users to remotely manage with the cloud server by implementing conversion between Modbus RTU and Modbus TCP of protocol communications. The proposed communication technique has been verified by experiments.

• Annual Conference of KIPS
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• 2017.04a
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• pp.673-676
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• 2017

Accompanying the Internet of Things (IoT) is a demand of advanced applications and services utilizing the potential of the IoT environment. Monitoring the environment for a provision of context-aware services to the human beings is one of the new trends in our future life. The IoTivity Cloud is one of the most notable open-source platform bringing an opportunity to collect, analyze, and interpret a huge amount of data available in the IoT environment. Based on the IoTivity Cloud, we aim to develop a novel platform for comprehensive monitoring of a future network, which facilitates on-demand data collection to enable the network behavior prediction and the quality of user experience maintenance. In consideration of performance evaluation of the monitoring platform, this paper presents results of a preliminary test on the data acquisition/supply process in the IoTivity Cloud.

• 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.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1159-1165
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• 2016

Traffic violations such as moving while the traffic lights are red have come from a simple omission to a premeditated act. The traffic control center cannot timely monitor all the cameras installed on the roads to trace and pursue those traffic violators. Modern vehicles are equipped and controlled by several sensors in order to support monitoring and reporting those kind of behaviors which some time end up in severe causalities. However, such applications within the vehicle environment need to provide security guaranties. In this paper, we address the limitation of previous work and present a secure and privacy preserving protocol for traffic violation reporting system in vehicular cloud environment which enables the vehicles to report the traffic violators, thus the roadside clouds collect those information which can be used as evidence to pursue the traffic violators. Particularly, we provide the unlinkability security property within the proposed protocol which also offers lightweight computational overhead compared to previous protocol. We consider the concept of conditional privacy preserving authentication without pairing operations to provide security and privacy for the reporting vehicles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4311-4330
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• 2015

Cloud computing has become a new paradigm by enabling on-demand provisioning of applications, platforms or computing resources for clients. Workflow scheduling has always been treated as one of the most challenging problems in clouds. Commercial clouds have been widely used in scientific research, such as biology, astronomy and weather forecasting. Certainly, it is very important for a cloud service provider to pursue the profits for the commercial essence of clouds. This is also significantly important for the case of providing services to workflow tasks. In this paper, we address the issues of workflow scheduling in commercial clouds. This work takes the communication into account, which has always been ignored. And then, a topology-based workflow-scheduling algorithm named Resource Auction Algorithm (REAL) is proposed in the objective of getting more profits. The algorithm gives a good performance on searching for the optimum schedule for a sample workflow. Also, we find that there exists a certain resource amount, which gets the most profits to help us get more enthusiasm for further developing the research. Experimental results demonstrate that the analysis of the strategies for most profits is reasonable, and REAL gives a good performance on efficiently getting an optimized scheme with low computing complexity.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.7
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• pp.633-641
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• 2015

In this study, we proposed a three-dimensional (3D) scanning system based on laser-vision technique and rotary mechanism for automatic 3D model reconstruction. The proposed scanning system consists of a laser projector, a camera, and a turntable. For laser-camera calibration a new and simple method was proposed. 3D point cloud data of the surface of scanned object was fully collected by integrating extracted laser profiles, which were extracted from laser stripe images, corresponding to rotary angles of the rotary mechanism. The obscured laser profile problem was also solved by adding an addition camera at another viewpoint. From collected 3D point cloud data, the 3D model of the scanned object was reconstructed based on facet-representation. The reconstructed 3D models showed effectiveness and the applicability of the proposed 3D scanning system to 3D model-based applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4849-4864
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• 2019

Modern applications such as augmented reality, connected vehicles, video streaming and gaming have stringent requirements on latency, bandwidth and computation resources. The explosion in data generation by mobile devices has further exacerbated the situation. Mobile Edge Computing (MEC) is a recent addition to the edge computing paradigm that amalgamates the cloud computing capabilities with cellular communications. The concept of MEC is to relocate the cloud capabilities to the edge of the network for yielding ultra-low latency, high computation, high bandwidth, low burden on the core network, enhanced quality of experience (QoE), and efficient resource utilization. In this paper, we provide a comprehensive overview on different traits of MEC including its use cases, architecture, computation offloading, security, economic aspects, research challenges, and potential future directions.

• Journal of Information Technology Applications and Management
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• v.27 no.4
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• pp.21-36
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• 2020

E-commerce represents the acquisition and sale, or the transmission of funds or data through an electronic platform. E-commerce is a paradigm shift that influences marketers and customers to improve current market processes. The significant challenges in e-commerce are the accuracy and performance factors during a business transaction, which has been substantially enhanced using Cloud Computing Techniques (CCT). The growth of e-commerce management has been increased due to massive internet penetration, and particularly small and emerging companies are increasingly using this alternative as a differentiated business model. E-commerce has significant environmental impacts and highly utilized in today's market scenario. Further, the replacement has not been thoroughly explored. Current research has been carried out to describe the e-commerce scenario to analyze market trends. This study further discusses the essential variables to the performance of market models for e-commerce. For example, e-procurement of products/services, electronic supply chain management, e-distribution and selling support (supplier connections, e-fulfilment) and online e-auctions (transactional) can represent important e-commerce capabilities, which can contribute to marketing strategy implementation effectiveness, resulting in higher export performance.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.555-566
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• 2012

The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.

• Journal of KIISE
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• v.42 no.8
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• pp.954-960
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• 2015

It is important to improve the performance of storage in the home cloud environment within the virtualized IoT gateway since the performance of applications deeply depends on storage. Though SSD caching is applied in order to improve the storage, it is only used for read-cache due to the limitations of SSD such as poor write performance and small write endurance. However, it is important to improve performance of the write operation in the home cloud server, in order to improve the end-user experience. This paper propose a novel SSD caching which considers write-data as well as read-data. We validate the enhancement in the performance of random-write by transforming it to the sequential patterns.