• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.164-167
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• 2019

차량 네트워크의 핵심 기술인 V2X 발전에 따라, V2I에서 중요한 역할을 하는 RSU에 대한 연구 또한 진행되고 있다. 그러나 기존 RSU 는 저성능 및 유지보수 고비용의 문제점이 존재하여 차량이 RSU 기능을 수행하는 mRSU가 제안되었다. 이에 mRSU를 배치하는 연구는 진행되고 있으나 mRSU 역할을 하는 차량을 선정하기 전, 해당 차량의 안전성을 판단하는 방안이 존재하지 않아 보안에 취약하다는 한계가 있다. 이를 해결하기 위해 본 논문에서는 차량을 mRSU 로 선정하기 전 교통 관제 센터에서 해당 차량의 안전성을 판단하고, mRSU 적합도를 수치화하여 이 데이터를 블록체인으로 저장 및 관리하는 방안에 대해 제안한다. 이를 통해 신뢰 적인 기관의 검증된 데이터의 무결성을 보장하여 보안 취약성을 보완할 수 있다는 장점이 존재한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.124-126
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• 2013

대량의 메모리, 네트워크 장치, 저장매체, CPU 등으로 구성된 데이터 센터의 운용에 있어서 시스템 구축이나 운용을 단순화하기 위한 가상화가 고려되고 있다. 특히 금융 분야와 같이 데이터의 폭증 시대에 대응하기 위한 분산 서버 노드의 메모리 가상화 시스템을 고려할 수 있으며 본 연구에서는 이러한 메모리 가상화 시스템을 운용하는데 있어서 지연을 최소화하기 위한 인피니밴드의 활용방안에 대하여 검토한다. 인피니밴드의 메모리 접속 기능인 RDMA (Remote Direct Memory Access)를 더욱 쉽게 사용하기 위한 사용자 친화적인 라이브러리 구현 방법을 제안하며 RDMA 사용 시 발생하는 지연 현상을 분석하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.269-270
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• 2022

빅데이터, 인공지능, 로봇공학, 사물인터넷 등 다양한 정보통신 기술의 융합으로 이루어지는 제4차 산업혁명이 부각과 함께 발생하는 데이터를 안전하게 관리 및 보관하면서 사용할 수 있는 클라우드 플랫폼에 대한 중요성도 같이 증가하고 있다. 그에 따라 신규로 클라우드 플랫폼을 구축하는 곳도 있지만, 기존 인프라를 유지하면서 신규 인프라를 추가하는 형태로 클라우드 플랫폼을 구축하는 경우도 많다. 클라우드 플랫폼을 신규 또는 추가 구축하는 경우 고려해야 할 사항을 인프라 리소스 측면과 클라우드 플랫폼 측면에서 살펴보고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.372-372
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• 2020

사회가 다원화되고 발달하면서 생활환경과 행동양식에 따라 홍수 등의 수난(水難) 으로 인한 피해 정도와 양상은 크게 달라질 수 있으나, 수난으로 인한 체감 가능한 피해의 정도와 규모는 예측이 어려운 현실이다. 그리고, 최근 인터넷과 소셜 네트워크 서비스(SNS)의 급진적 발달은 재난 관리에 대중적 지식을 수집하여 활용하도록 촉진하고 있고, 이로 인해 재난 상황에서 '대중적인 정보가 기술자에 의해 어떻게 얼마나 신중하게 고려되어야 하는지와 어떻게 과학적으로 해석해야하는지'가 핵심 쟁점으로 부상하고 있다. 본 연구에서는 최근 널리 사용되는 인공지능 및 딥러닝 기법을 조사 분석하였다. 분석을 통해 수문 예측 분야에서 이러한 기술이 적용된 사례와 신기술을 조망해 보고 기존 기술이 인공지능 및 딥러닝 기법의 적용으로 대체 가능한 정도를 가늠해 보았다.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.9-15
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• 2021

With the recent development of 5G and artificial intelligence technologies, it is interested in AIOT technology to collect, process, and analyze information in cloud edge environments. AIIoT technology is being applied to various smart environments, but research is needed to perform fast response processing through accurate analysis of collected information. In this paper, we propose a technique to minimize bandwidth and processing time by blocking the connection processing between AIOT information through fast processing and accurate analysis/forecasting of information collected in the smart environment. The proposed technique generates seeds for data indexes on AIOT devices by multipointing information collected by blockchain, and blocks them along with collection information to deliver them to the data center. At this time, we deploy Deep Neural Network (DNN) models between cloud and AIOT devices to reduce network overhead. Furthermore, server/data centers have improved the accuracy of inaccurate AIIoT information through the analysis and predicted results delivered to minimize latency. Furthermore, the proposed technique minimizes data latency by allowing it to be partitioned into a layered multilayer network because it groups it into blockchain by applying weights to AIOT information.

• The Journal of Bigdata
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• v.4 no.2
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• pp.159-173
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• 2019

Last-Mile delivery optimization plays a key role in the urban supply chain operation, which is the most expensive and time-consuming and most complicated part of the whole delivery process. The urban consolidation center (UCC) is regarded as a significant asset for supporting customer demand in the last-mile delivery service. It is the key benefit of UCC to improve the load balance of vehicles and to reduce the total traveling distance by finding the better route with the well-organized multi-leg vehicle journey in the urban area. This paper presents the model using multiple scenario analysis integrated with mathematical optimization techniques using Geographic Information System (GIS). The model aims to find the best solution for the distribution network consisted of DC and UCC, which is applied to the case of Ulaanbaatar Mongolia. The proposed methodology integrates two sub-models, location-allocation model and vehicle routing problem. The multiple scenarios devised by selecting locations of UCC are compared considering the general performance and delivery patterns together. It has been adopted to make better decisions the quantitative metrics such as the economic value of capital cost, operating cost, and balance of using available resources. The result of this research may help the manager or public authorities who should design the distribution network for the last mile delivery service optimization using UCC within the urban area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.247-253
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• 2008

In this paper, we describes the design and implementation of real-time management system for efficient operation via monitoring and control of MCC(Motor Control Center). The real-tine management system can be divided hardware(MCC panel) and software(management program). First, hardware is divided into load attaching motor and MCC components for working together control and data network. Second, software(management system) are consisted of communication interface, environment setting, data processing modules. The produced and implemented reduction model of MCC panel is pretested using m-PRO, iM-PRO devices, and HyperTerminal. For field test, MCC panel is tested by RS-232C/485, communication procedure in management system is certified by transmitting and receiving message using control command. By the experimental results, the implemented real-time management system can be used to operate MCC system.

• The Journal of Bigdata
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• v.8 no.2
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• pp.27-36
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• 2023

The logistics industry is becoming increasingly important as it is closely linked to our daily lives, storing and transporting the goods and resources that businesses and consumers need. With its growing importance, the logistics industry strives to provide efficient and sustainable services through innovations and artificial intelligence are being used to optimize logistics networks, make transport more environmentally friendly, and more. Research and improvements are being undertaken in various domains, such as logistics network optimization and environmentally friendly transportation through technological innovation and artificial intelligence; however, there still needs to be more research in certain aspects of the logistics industry. In particular, devising an optimized stowage plan for vehicle carriers, considering various factors, involves a significant degree of complexity and remains an under-researched area. This paper studies the loading and unloading algorithms that enable to quickly and efficiently establish stowage plans for vehicle carriers, reflecting a variety of considerations and rules for stowage planning.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.416-429
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• 2018

Typhoons and floods are natural disasters that occur frequently, and the damage resulting from these disasters must be in advance predicted to establish appropriate responses. Direct damages such as building collapse, human casualties, and loss of farms and fields have more attention from people than indirect damages such as increase of consumer prices. But indirect damages also need to be considered for living. The agricultural products are typical consumer items affected by typhoons and floods. Sudden, powerful typhoons are mostly accompanied by heavy rains and damage agricultural products; this increases the retail price of such products. This study analyzes the influence of natural disasters on the price of agricultural products by using a deep learning algorithm. We decided rice, onion, green onion, spinach, and zucchini as target agricultural products, and used data on variables that influence the price of agricultural products to create a model that predicts the price of agricultural products. The result shows that the model's accuracy was about 0.069 measured by RMSE, which means that it could explain the changes in agricultural product prices. The accurate prediction on the price of agricultural products can be utilized by the government to respond natural disasters by controling amount of supplying agricultural products.

• The Journal of Bigdata
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• v.6 no.1
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• pp.115-125
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• 2021

Due to various ICT Technology innovations and Digital Transformation, the Internet of Things(IoT) environment is increasingly requiring intelligence, decentralization, and automated service, especially an advanced and stable smart service environment in the Industrial Internet of Things(IIoT) where communication network(5G), data analysis and artificial intelligence(AI), and digital twin technology are combined. In this study, we propose IIoT Edge middleware systems for flexible interface with heterogeneous devices such as facilities and sensors at various industrial sites and for quick and stable data collection and processing.