• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1368-1370
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• 1996

The Information of Edges which takes small area comparing with the total image is very important in DNA images as well as general images. DNA image is the object should be managed by computing and it's demanding information is less than general images, but the accuracy is more important In a huge DNA image processing system such as DNA Information Bank, the performance depends on the size of image. In this paper, we extract the edge information and make it as a binary image. To reduce the size of the original image, it was applied by JPEG image compression method. The compressed image is combined with edge information when they are restored. As a result, Both the image compression ratio and restoration quality are optimized without the loss of critical information.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 B
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• pp.262-264
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• 2000

A numerical method for the analysis of 3D eddy current in conductors due to applied time varying field is suggested using the finite element method. In the approximation of the field quantifies, the edge element is used, because it reduce the required computer memory and the computing time compared with the nodal elements. With edge elements, furthermore, the field governing equations become simple because the electric scalar potential ${\phi}$ can be set to zero. The modified magnetic vector potential($A^*$) is used as a state variable. The analysed results are compared with the experimentally measured ones for the TEAM workshop problem3.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.443-451
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• 2023

Machine Learning has introduced many solutions in data science, but its application in IoT faces significant challenges, due to the limitations in memory size and processing capability of constrained devices. In this paper we design an automatic gamma radiation detection and identification embedded system that exploits the power of TinyML in a SiPM micro radiation sensor leveraging the Edge Impulse platform. The model is trained using real gamma source data enhanced by software augmentation algorithms. Tests show high accuracy in real time processing. This design has promising applications in general-purpose radiation detection and identification, nuclear safety, medical diagnosis and it is also amenable for deployment in small satellites.

• Journal of Information Processing Systems
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• 제18권6호
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• pp.803-812
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• 2022

With the increasing number of mobile device users worldwide, utilizing mobile edge computing (MEC) devices close to users for content caching can reduce transmission latency than receiving content from a server or cloud. However, because MEC has limited storage capacity, it is necessary to determine the content types and sizes to be cached. In this study, we investigate a caching strategy that increases the hit ratio from small base stations (SBSs) for mobile users in a heterogeneous network consisting of one macro base station (MBS) and multiple SBSs. If there are several SBSs that users can access, the hit ratio can be improved by reducing duplicate content and increasing the diversity of content in SBSs. We propose a Deep Q-Network (DQN)-based caching strategy that considers time-varying content popularity and content redundancy in multiple SBSs. Content is stored in the SBS in a divided form using maximum distance separable (MDS) codes to enhance the diversity of the content. Experiments in various environments show that the proposed caching strategy outperforms the other methods in terms of hit ratio.

• Journal of information and communication convergence engineering
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• 제21권4호
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• pp.329-336
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• 2023

This paper introduces an edge AI-based scene-specific object detection system for long-term traffic management, focusing on analyzing congestion and movement via cameras. It aims to balance fast processing and accuracy in traffic flow data analysis using edge computing. We adapt the YOLOv5 model, with four heads, to a scene-specific model that utilizes the fixed camera's scene-specific properties. This model selectively detects objects based on scale by blocking nodes, ensuring only objects of certain sizes are identified. A decision module then selects the most suitable object detector for each scene, enhancing inference speed without significant accuracy loss, as demonstrated in our experiments.

• ETRI Journal
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• 제42권5호
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• pp.639-642
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• 2020

• 한국멀티미디어학회논문지
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• 제24권1호
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• pp.75-94
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• 2021

The 4th industrial revolution needs a fusion of artificial intelligence, robotics, the Internet of Things (IoT), edge computing, and other technologies. For the fusion of technologies, cloud computing technology can provide flexible and high-performance computing resources so that cloud computing can be the foundation technology of new emerging services. The emerging services become a global-scale, and require much higher performance, availability, and reliability. Public cloud providers already provide global-scale services. However, their services, costs, performance, and policies are different. Enterprises/ developers to come out with a new inter-operable service are experiencing vendor lock-in problems. Therefore, multi-cloud technology that federatively resolves the limitations of single cloud providers is required. We propose a software platform, denoted as Cloud-Barista. Cloud-Barista is a multi-cloud service common platform for federating multiple clouds. It makes multiple cloud services as a single service. We explain the functional architecture of the proposed platform that consists of several frameworks, and then discuss the main design and implementation issues of each framework. To verify the feasibility of our proposal, we show a demonstration which is to create 18 virtual machines on several cloud providers, combine them as a single resource, and manage it.

• Journal of Information Processing Systems
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• 제19권2호
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• pp.240-257
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• 2023

The industrial Internet of Things (IIoT) is characterized by intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. The heterogeneous IIoT devices require a high data rate, high reliability, high coverage, and low delay, thus posing a significant challenge to information security. High-performance edge and cloud servers are a good backup solution for IIoT devices with limited capabilities. However, privacy leakage and network attack cases may occur in heterogeneous IIoT environments. Cloud-based multi-party computing is a reliable privacy-protecting technology that encourages multiparty participation in joint computing without privacy disclosure. However, the default cloud selection method does not meet the heterogeneous IIoT requirements. The server can be dishonest, significantly increasing the probability of multi-party computation failure or inefficiency. This paper proposes a blockchain and smart contract-based optimized cloud node selection framework. Different participants choose the best server that meets their performance demands, considering the communication delay. Smart contracts provide a progressive request mechanism to increase participation. The simulation results show that our framework improves overall multi-party computing efficiency by up to 44.73%.

• 한국멀티미디어학회논문지
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• 제23권10호
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• pp.1258-1269
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• 2020

The IoT(Internet of Things) service provides users with valuable services by collecting and analyzing data using Internet-connected IoT devices. Currently, IoT service platforms are accomplished by using edge computing to reduce the delay time required to collect data from IoT devices. However, if a user moves to another network with IoT device, the connection will be lost and IoT service will be suspended. To solve this problem, we proposes a service that automatically roaming IoT service when IoT device makes move. IoT roaming service provides a device automatic tracking management technique designed to continue receiving IoT services even if users move to other networks. To check if the proposed roaming service was effective, we implemented IoT roaming service and measured the data transfer time while move between networks along with devices while using IoT service. As a result, the average data transfer time was 124.62ms, and the average service interrupt time was 812.12ms. with this result, we can assume that the user could feel service interruption time very shortly and it will not affect the service experience. with IoT roaming service, we expect that it will present a method that stably providing IoT services even if user moves networks.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.419-421
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.