• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.399-406
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• 2023

Cloud computing has been evolved to support edge computing architecture that combines fog management layer with edge servers. The main reason why it is received much attention is low communication latency for real-time IoT applications. At the same time, various cloud task scheduling techniques based on artificial intelligence have been proposed. Artificial intelligence-based cloud task scheduling techniques show better performance in comparison to existing methods, but it has relatively high scheduling time. In this paper, we propose a deep learning-based dynamic scheduling with multi-agents supporting scalability in edge computing environments. The proposed method shows low scheduling time than previous artificial intelligence-based scheduling techniques. To show the effectiveness of the proposed method, we compare the performance between previous and proposed methods in a scalable experimental environment. The results show that our method supports real-time IoT applications with low scheduling time, and shows better performance in terms of the number of completed cloud tasks in a scalable experimental environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.208-211
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• 2019

차량 포그 컴퓨팅 및 자율주행 자동차 개발 기술이 발전하면서 자동차 내부에 탑재된 IoT 센서들은 교통 정보 관련 다양한 정보를 수집할 수 있게 되었고, 더불어 자동차와 자동차간, 차량과 교통 인프라 간의 통신을 통해 수집된 교통 정보의 공유가 가능해졌다. 그러나 이 과정에서 알지 못하는 차량으로부터 받은 메시지를 어떻게 신뢰할 수 있는지에 대한 문제가 존재한다. 이를 보완하기 위해 평판 시스템을 적용한 연구들이 있으나 여전히 불안전한 데이터 저장방식과 통신 트래픽 문제가 존재한다. 이를 해결하기 위해 블록체인 기술을 사용된다. 본고에서는 블록체인 기반의 차량 네트워크의 평판 시스템 연구 사례를 분석한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.625-627
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• 2022

FEC (Fog/Edge Computing) 환경에서 지연시간 최소화는 로컬과 에지 서버 간의 효율적인 협력을 보장하기 위한 최적의 계산 오프로딩 방법 결정을 통해 실현될 수 있다. 본 논문은 임의의 응용 서비스 실행모듈에 대한 부분 오프로딩 기반의 로컬(모바일 장치)과 에지 서버 간의 협업 경로를 추출하는 방법을 제안한다. 제안 방법은 다중 분기구조를 포함하는 응용 서비스 실행모듈에 대한 부분 오프로딩 기반의 최적 협업 실행경로 추출 방법을 제안한다. 제안 방법은 각 부분 모듈들의 실행위치에 따라 변화되는 지연시간 측정 및 분석에 적용가능하다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.162-169
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• 2022

In a dynamically changing time-varying network environment, the optimal moving pattern of edge devices can be applied to distributing computing resources to edge cloud servers or deploying new edge servers in the FEC(Fog/Edge Computing) environment. In addition, this can be used to build an environment capable of efficient computation offloading to alleviate latency problems, which are disadvantages of cloud computing. This paper proposes an algorithm to extract the optimal moving pattern by analyzing the moving path of multiple edge devices requiring application services in an arbitrary spatio-temporal environment based on frequency. A comparative experiment with A^* and Dijkstra algorithms shows that the proposed algorithm uses a relatively fast execution time and less memory, and extracts a more accurate optimal path. Furthermore, it was deduced from the comparison result with the A^* algorithm that applying weights (preference, congestion, etc.) simultaneously with frequency can increase path extraction accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1551-1558
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• 2022

We propose a two-tier cooperative computing system comprised of a mobile device and an edge server for partial offloading of multi-branch structures in Fog/Edge Computing environments in this paper. The proposed system includes an algorithm for splitting up application service processing by using reconstructive linearization techniques for multi-branch structures, as well as an optimal collaboration algorithm based on partial offloading between mobile device and edge server. Furthermore, we formulate computation offloading and CNN layer scheduling as latency minimization problems and simulate the effectiveness of the proposed system. As a result of the experiment, the proposed algorithm is suitable for both DAG and chain topology, adapts well to different network conditions, and provides efficient task processing strategies and processing time when compared to local or edge-only executions. Furthermore, the proposed system can be used to conduct research on the optimization of the model for the optimal execution of application services on mobile devices and the efficient distribution of edge resource workloads.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1571-1576
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• 2018

Recently, the attractive changes of mobile device are a improvement of the computing performance, dramatic improvement of storage capacity, constant connection to the internet, and sophisticated development of display technology. As a result, database applications utilizing mobile devices are emerging. These applications include databases for mobile servers, databases for edge computing, and fog computing. Therefore, it is important to pay attention to the current mobile database and pay attention to whether it has suitable performance for the applications. In this paper, the most common mobile database, SQLite3 is selected and experimented to test and understand the update performance and characteristics. The results of experiment are compared with the one of Oracle database at the same condition to evaluate the experiment. As a result, Insert Performance of SQLite3 has a lot of points to be improved and Update performance is very good. Especially, the performance of Range Query is excellent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1117-1122
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• 2020

The improving performance and utilizing application fields of mobile devices are getting bigger and wider. With this trend, applications that use database engines on mobile devices are also becoming common. Applications requiring mobile databases include mobile server databases, edge computing, fog computing, and the like. By the way, the most representative and widely used mobile database is SQLite3. In this paper, we test and compare the update performance of SQLite3 by some file systems. The update performance of the file systems in the mobile environment is an important performance factor in the limited H/W environment. The comparison file system was chosen as FAT, Ext2, and NTFS. Under the same conditions, experiments with each file system to test update performance and characteristics were processed. From the experimental results, we could analyze the advantages and disadvantages of each file system for each database update pattern.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1928-1939
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• 2017

Fog computing is another paradigm of the cloud computing, which extends the ubiquitous services to applications on many connected devices in the IoT (Internet of Things). In general, if we access a lot of IoT devices with existing cloud, we waste a huge amount of bandwidth and work efficiency becomes low. So we apply the paradigm called fog between IoT devices and cloud. The network architecture based on cloud and fog computing discloses the security and privacy issues according to mixed paradigm. There are so many security issues in many aspects. Moreover many IoT devices are connected at fog and they generate much data, therefore light and efficient security mechanism is needed. For example, with inappropriate encryption or authentication algorithm, it causes a huge bandwidth loss. In this paper, we consider issues related with data encryption and authentication mechanism in the network architecture for cloud and fog-based M2M (Machine to Machine) IoT services. This includes trusted encryption and authentication algorithm, and key generation method. The contribution of this paper is to provide efficient security mechanisms for the proposed service architecture. We implemented the envisaged conceptual security check mechanisms and verified their performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.212-215
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• 2018

현재 자동차 사고 보험에서는 보험사기 문제가 해결되지 못하고 있다. 매년 자동차 보험 회사의 보험사기로 인한 금전적 손해는 증가하고 있다. 또한 보험사기를 막기 위해 적용되는 필수적인 보험 회사 직원의 현장 방문은 비효율적이고 보험금을 받을 때까지 많은 시간을 소모한다. 이를 해결하기 위해 자동차 보험에 블록체인을 적용한 go2solution은 기존 보험 처리 과정을 단축시켰지만 보험청구자의 사진만으로 사고 발생을 판단하기 때문에 사고를 입증하는데 증거가 부족하고 이를 이용한 보험 사기가 가능하다. 따라서 사고 발생 여부의 신뢰도를 측정하여 보험사기를 방지할 수 있도록 블록체인 기반 자동차 보험 신뢰모델을 제안한다. 포그 컴퓨팅을 적용하여 차량, 보험회사, RSU의 정보 공유를 원활하게 한다. 또한 목격자들이 신뢰요소로 적용될 수 있도록 블록체인 컨소시엄을 통한 인센티브 시스템을 적용하여 목격자들은 적극적으로 사고정보를 제공한다. 이렇게 수집된 다양한 신뢰요소 데이터를 분석하여 신뢰점수와 등급을 정한다. 이때 회귀분석을 적용하여 각각의 신뢰요소의 중요도에 따라 다른 가중치를 적용하여 정확한 신뢰점수를 책정한다. 결과적으로 보험회사는 보험사기 피해액을 절감하고 보험청구자는 인센티브를 사용하여 적은 보험료를 지불한다.