• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.779-780
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• 2015

As IoT becomes a main technology of the age, many IoT products have developed and are being developed now. By using open-source hardware "Arduino"and open-source IoT platform "Temboo" to analize CAN signal from vehicle and make vehicle IoT environment to analize and use it through the mobile phone, figured out the way to develop the IoT environment with low cost. Also suggest the way to solve problems and improove.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.291-296
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• 2021

The development of the Internet of Things(IoT) requires large computational resources for tasks from numerous devices. Mobile Edge Computing(MEC) has attracted a lot of attention in the IoT environment because it provides computational resources geographically close to the devices. Task offloading to MEC servers is efficient for devices with limited battery life and computational capability. In this paper, we assumed an industrial IoT environment requiring high reliability. The complexity of optimization problem in industrial IoT environment with many devices and multiple MEC servers is very high. To solve this problem, the problem is divided into two. After selecting the MEC server considering the queue status of the MEC server, we propose an offloading decision algorithm that optimizes reliability and energy consumption using genetic algorithm. Through experiments, we analyze the performance of the proposed algorithm in terms of energy consumption and reliability.

• Journal of Korea Game Society
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• v.16 no.3
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• pp.87-96
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• 2016

As use of Internet increase, IoT(Internet Of Things), a interaction between connected devices, is widely used throughout industrial area. In this paper, we discussed what to consider when planning framework for contents using user's mobile devices and various sensors in IoT environment and suggest related techniques. Also, using the techniques suggested in this paper, we showed the prototype of the framework. Finally, we showed the possibility of games in the IoT environment by creating game in the IoT environment.

• Journal of KIISE
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• v.42 no.6
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• pp.807-816
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• 2015

The Internet of Things (IoT) has recently been showered with much attention worldwide. Various kinds of devices, communicating with each other in the IoT, demand multiple communication technologies to coexist. In this environment, mobile devices may utilize the vertical handover between different wireless radio interfaces such as Wi-Fi and Bluetooth, for efficient data transfer. In this paper, an IoT broker is implemented to support the vertical handover, which can also support and manage heterogeneous devices and communication interfaces. The handover is activated based on RSSI, Link Quality values, and real time traffic. The experimental results show that the proposed handover system substantially improves QoS in Bluetooth and reduces power consumption in mobile devices as compared with a system using only Wi-Fi.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.400-403
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• 2021

As IoT technology becomes popular, more and more data is being generated, and the diversity of data is also increasing. In particular, in smart factory or Home IoT systems, data processing is very important because various data is collected and processed in real time through sensors. In this paper, we present a method for collecting, analyzing, and monitoring various data generated by sensors in IoT environment through Raspberry Pi. We also validate its usefulness by demonstrating that the above processed data can be operated in conjunction with smart mirror and mobile application.

• Journal of Web Engineering
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• v.19 no.1
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• pp.29-62
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• 2020

In highly dynamic IoT environments, the connection statuses of IoT resources and the availability of IoT-based services change frequently. Therefore, to successfully build distributed service registries for managing and finding the information about available services in an effective manner, it is crucial to minimize the overhead of message exchanges between registries and to reduce the time overhead for identifying the capabilities of available IoT resources and the services that can be provided by utilizing these capabilities. In this paper, we propose a lightweight messaging approach that uses hierarchical Bloom filters to efficiently represent service information to be exchanged and managed by distributed service registries for IoT environments with high mobility. We also propose a method for serializing the dimensions of a Bloom-filter-encoded search space. We conducted experiments to demonstrate the improvement in the service discovery performance, the reduction in message traffic among service registries, and the decrease in the latency when synchronizing distributed service registries.

• Annual Conference of KIPS
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• 2021.05a
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• pp.202-204
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• 2021

다양한 IoT 기기로 구성된 모바일 IoT 환경에서는 IoT에서 수집된 데이터가 다른 IoT의 학습 데이터로 사용되는 순환 구조로 이루어져 있다. 따라서 해당 환경에서 데이터는 공유되는 자원이며 매우 중요한 요소이다. 특히 IoT 기기가 밀집된 지역에서는 많은 트래픽이 발생하기 때문에 전송지연 및 데이터 손실로 인한 시스템 성능이 저하되는 문제가 발생한다. 따라서 본 논문에서는 안전한 데이터 통신을 위한 블록체인 기반의 시스템 구조를 제안한다. 해당 시스템은 블록체인을 사용하여 IoT 기기의 이동성과 밀집도를 판별하고, 트래픽 밀집 구역이 발생하였을 경우 UAV를 활용하여 통신이 원활하게 이루어질 수 있도록 한다.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.501-505
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• 2016

Recently, the frequency of dealing important information regarding financial services like paying through smart device or internet banking on smart device has been increasing. Also, with the development of smart device execution environment towards open software environment, it became easier for users to download and use random application software, and its security aspect appears to be weakening. This study inspects features of hardware-based smart device security technology. Furthermore, this study proposes a realization method in MTM hardware-based secure smart device execution environment for an application software that runs in smart devices. While existing MTM provides the root of trust function only for the mobile device, the MTM-based mobile security environment technology proposed in this paper can provide numerous security functions that application program needs in mobile device. The further researches on IoT devices that are compatible with security hardware, gateway security technology and methods that secure reliability and security applicable to varied IoT devices by advancing security hardware are the next plan to proceed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.2
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• pp.199-208
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• 2017

IoT, Cloud, Bigdata, Mobile, AI, and 3D print, which are called as the main axis of the 4th Industrial Revolution, can be predicted to be changed when the technology is applied to the military. Especially, when I think about the purpose of battle, I think that IoT, Cloud, Bigdata, Mobile, and AI will play many role. Therefore, in this paper, Smart Military is defined as the future military that incorporates these five technologies, and the architecture is established and the appropriate information security model is studied. For this purpose, we studied the existing literature related to IoT, Cloud, Bigdata, Mobile, and AI and found common elements and presented the architecture accordingly. The proposed architecture is divided into strategic information security and tactical information security in the Smart Military environment. In the case of vulnerability, the information security is divided into strategic information security and tactical information security. If a protection system is established, it is expected that the optimum information protection can be constructed within an effective budget range.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.1-9
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• 2018

In the fourth industrial revolution, which has become an issue now, we have been able to receive instant analysis results faster than the existing slow speed through various Big Data technologies, and to conduct real-time monitoring on mobile and web. First, various irregular sensor Data is generated using IoT device, Raspberry Pi. Sensor Data is collected in real time, and the collected data is distributed and stored using several nodes. Then, the stored Sensor Data is processed and refined. Visualize and output the analysis result after analysis. By using these methods, we can train the human resources required for Big Data and mobile related fields using IoT, and process data efficiently and quickly. We also provide information that can confirm the reliability of research results through real time monitoring.