• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.678-680
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• 2013

Recently, A computing environment are provided that can easily be used for services based on the cloud environment. Among them, SaaS(SoftWare as a Service) is that it provides cloud users to be available by placing the cloud systems on the Internet software. But, the problem with this, problems is that user can not be utilized to not find a service registered in the cloud system. The thing to make clear the meaning and relationship between services using the ontology to solve these problems, It must be supported to be used to find the exact service the user wants. Ontology for service discovery can be used to help to find services by guessing relevance by using the function or service names entered by the user. We provide how to configure the service ontology and the search system of services using ontology.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.23-29
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• 2022

Digital services improve existing ways of purchasing contracts. In this study, we empirically analyzed the effects of individual technology readiness (optimism, innovation, inconvenience, anxiety) on the acceptance intention of cloud computing technology for users with relatively high understanding of cloud service. Also, the effect of technology readiness on acceptance intention was verified by the mediating effect of digital conversion. As a result, optimism and innovation had a positive effect on digital conversion, and discomfort and anxiety had a negative effect on digital conversion. And although the partial mediating effect of digital conversion was verified in the relationship between optimism, anxiety and acceptance intention, it was verified that there was no mediating effect of digital conversion in the relationship between innovation, discomfort and acceptance intention. Through these results, the practical implications and future research directions of cloud services were presented to companies.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.103-111
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• 2019

The IoT-driven large-scaled systems consist of connected things with on-chip executable embedded software. These light-weighted embedded things have limited hardware space, especially small size of on-chip flash memory. In addition, on-chip embedded software in flash memory is not easy to update in runtime to equip with latest services in IoT-driven applications. It is becoming important to develop light-weighted IoT devices with various software in the limited on-chip flash memory. The remote instruction execution in cloud via IoT connectivity enables to provide high performance software execution with unlimited software instruction in cloud and low-power streaming of instruction execution in IoT edge devices. In this paper, we propose a Cloud-IoT asymmetric structure for providing high performance instruction execution in cloud, still low power code executable thing in light-weighted IoT edge environment using remote instruction execution. We propose a simulated approach to determine efficient partitioning of software runtime in cloud and IoT edge. We evaluated the instruction cloudification using remote instruction by determining the execution time by the proposed structure. The cloud-connected instruction set simulator is newly introduced to emulate the behavior of the processor. Experimental results of the cloud-IoT connected software execution using remote instruction showed the feasibility of cloudification of on-chip code flash memory. The simulation environment for cloud-connected code execution successfully emulates architectural operations of on-chip flash memory in cloud so that the various software services in IoT can be accelerated and performed in low-power by cloudification of remote instruction execution. The execution time of the program is reduced by 50% and the memory space is reduced by 24% when the cloud-connected code execution is used.

• Convergence Security Journal
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• v.22 no.2
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• pp.67-75
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• 2022

Due to the COVID-19 pandemic, many companies have introduced remote work. However, the introduction of remote work has increased attacks on companies to access sensitive information, and many companies have begun to use cloud services to respond to security threats. This study used LDA topic modeling techniques by collecting news data with the keyword 'cloud security' to analyze changes in domestic cloud security trends before and after the COVID-19 pandemic. Before the COVID-19 pandemic, interest in domestic cloud security was low, so representation or association could not be found in the extracted topics. However, it was analyzed that the introduction of cloud is necessary for high computing performance for AI, IoT, and blockchain, which are IT technologies that are currently being studied. On the other hand, looking at topics extracted after the COVID-19 pandemic, it was confirmed that interest in the cloud increased in Korea, and accordingly, interest in cloud security improved. Therefore, security measures should be established to prepare for the ever-increasing usage of cloud services.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.331-337
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• 2014

Paradigm shift to cloud computing has increased the importance of security. Even though public cloud computing providers such as Amazon, already provides security related service like firewall and identity management services, it is not suitable to protect data in cloud environments. Because in public cloud computing environments do not allow to use client's own security solution nor equipments. In this environments, user are supposed to do something to enhance security by their hands, so the needs of visualized security management arises. To implement visualized security management, developing near realtime data handling & packet classification mechanisms are crucial. The key technical challenges in packet classification is how to classify packet in the manner of unsupervised way without human interactions. To achieve the goal, this paper presents automated packet classification mechanism based on naive-bayesian and packet Chunking techniques, which can identify signature and does machine learning by itself without human intervention.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.2
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• pp.63-76
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• 2012

The possibility of successful commercialization of technologically innovative products depends on the degree to which consumers select and utilize the product. Therefore, the research that endeavors to find the usage behavior and the acceptance intention of users of technologically innovative products is a very important quest. This study empirically analyzes the factors that influence commercialization of a technologically innovative product: cloud computing. Existing studies examined acceptance intentions by expanding the TAM model and excluded attitude and usage behavior. This study determined attitude, usage behavior and personal characteristics of consumers to be important influencing factors. The results of the empirical analysis are as follows: First, the self-efficacy of personal characteristics had a significant effect on ease of use and acceptance intention and perceived costs had a significant influence on the factors of perceived usefulness and perceived ease of use. Second, research on the systematic characteristics of cloud computing confirmed that security was an important factor affecting acceptance intention while innovativeness was critical to ease of use. Third, of the usage characteristics among users of technologically innovative products, perceived usefulness had an effect on the acceptance and usage behavior of cloud computing, and perceived ease of use had an important influence on perceived usefulness. Currently, when cloud computing services have not yet become widespread to the public, this study proposed meaningful results for policy direction and commercialization strategies by revealing variables that influence acceptance and usage behavior.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.39-46
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• 2024

An API gateway is a high-availability component that provides a single entry point for API clients outside the cloud to connect with services inside the cloud. It has a high risk of creating bottlenecks and requires redeployment when services change. The Java language, in which several API gateways are implemented, announced technologies called GraalVM Native Image and Virtual Thread to overcome problems with deployment and operational performance. Applying these technologies to Java applications requires changes to the source code and deployment procedures. In this study, the performance of the API gateway was measured and analyzed when it operated based on GraalVM Native Image and Java Virtual Machine(JVM) and between Virtual Thread and Reactive thread processing methods. In this study, evaluation indicators were selected to evaluate deployment performance and operational performance, and the performance of the evaluation indicators was measured and evaluated in four environments.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.301-307
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• 2012

The development of mobile devices and the spread of wireless network help share and exchange information and resources more easily. The bond them to Cloud Computing technology help pay attention to "Mobile Cloud" service, so there have been being a lot of studies on "Mobile Cloud" service. Especially, the important of 'Personalization Service' which is customized for each user's preference and context has been increasing. In order to provide appropriate personalization services, it enables to recognize user's current state, analyze the user's profile like user's tendency and preference, and draw the service answering the user's request. Most existing frameworks, however, are not very suitable for mobile devices because they were proposed on the web-based. And other context information except location information among user's context information are not much considered. Therefore, this paper proposed the context-aware framework, which provides more suitable services by using user's context and profile.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.139-147
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• 2011

There is a growing tendency toward a vehicle demand and a utilization of traffic information systems. Due to various kinds of traffic information systems and increasing of communication data, the traffic information service requires a very high IT infrastructure. A cloud computing environment is an essential approach for reducing a IT infrastructure cost. And the traffic information service needs a provisioning scheduling method for managing a resource. So we propose a provisioning scheduling with conditional probability inference (PSCPI) for the traffic information service on cloud environment. PSCPI uses a naive bayse inference technique based on a status of a virtual machine. And PSCPI allocates a job to the virtual machines on the basis of an availability of each virtual machine. Naive bayse based PSCPI provides a high throughput and an high availability of virtual machines for real-time traffic information services.