• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5290-5304
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• 2016

With the growth of the massive amount of data, the failure probability of the cloud storage node is becoming more and more big. A single fault tolerance strategy, such as replication and erasure codes, has some unavoidable disadvantages, which can not meet the needs of the today's fault tolerance. Therefore, according to the file access frequency and size, an adaptive hybrid redundant fault tolerance strategy is proposed, which can dynamically change between the replication scheme and erasure codes scheme throughout the lifecycle. The experimental results show that the proposed scheme can not only save the storage space(reduced by 32% compared with replication), but also ensure the fast recovery of the node failures(increased by 42% compared with erasure codes).

• 소성∙가공
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• 제12권6호
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• pp.542-549
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• 2003

Three-dimensional forging analysis becomes an inevitable tool to make design process more reliable and more producible. In this study, in order to make the investigation for three-dimensional forging analysis more conveniently and accurately, a new post processor was developed. For post-processing of multi-stage forging simulation, efficient data structure was proposed and applied by using STL. New file architecture was developed to handle successive and huge data efficiently, common in three-dimensional forging analysis. Since sectioning and flow tracing plays an important role in the investigation of analysis result, we developed an algorithm suitable for 4-node and 10-node tetrahedron. This flow tracing algorithm can trace and reverse-trace flow through remeshing. Developed program shows good performance and functionality. Especially, a big size problem can be handled easily due to proposed data structure and file architecture.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.1-7
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• 2019

In this paper, we implemented a Wi-Fi based cluster system using raspberry pi for multidisciplinary education. The cluster implementation on the desktop was more difficult to maintain the complexity, big size, high price, power consumption as the number of nodes increased. In this paper, we implemented a cluster using Raspberry Pi, which is developed for educational purposes, to reduce the cost of connecting nodes. In addition, the complexity of system construction is reduced by replacing the connection between each node with Wi-Fi. Also, the inconvenience of configuration due to node increase was reduced. It is expected that the implementation of the cluster will be a good alternative in the educational environment where distributed processing and parallel processing are performed in the embedded environment. Also, it is confirmed that it can be applied to the multidisciplinary education.

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1035-1043
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• 2021

An Internet of Things (IOT) sensor network is an effective solution for monitoring environmental conditions. However, IOT sensor networks generate massive data such that the abilities of massive data storage, processing, and query become technical challenges. To solve the problem, a Hadoop cloud platform is proposed. Using the time and workload genetic algorithm (TWLGA), the data processing platform enables the work of one node to be shared with other nodes, which not only raises efficiency of one single node but also provides the compatibility support to reduce the possible risk of software and hardware. In this experiment, a Hadoop cluster platform with TWLGA scheduling algorithm is developed, and the performance of the platform is tested. The results show that the Hadoop cloud platform is suitable for big data processing requirements of IOT sensor networks.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2023년도 제67차 동계학술대회논문집 31권1호
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• pp.153-154
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• 2023

대한민국의 교통 혼잡 비용은 2018년 기준 67조 원으로 국내총생산(GDP)의 3.6%를 차지하고 있다. 또한 국민 교통 고통지수는 매년 상승하고 있는 추세이다. 본 논문에서는 인구 밀집도가 가장 높은 서울시의 교통 혼잡 문제를 해결하기 위해 빅데이터 분석을 통한 효과적인 정책을 제공하고자 한다. 국가 표준 링크 아이디(LINK_ID)와 노드 아이디(NODE_ID)를 통해 위도 경도 데이터를 추출하고, 정체성이 높은 도로를 시각화해 추려진 특성과 공통점을 파악한다. 이를 토대로 정체성을 낮출 방안을 제공하고자 한다.

• 융합보안논문지
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• 제12권1호
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• pp.3-8
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• 2012

고정된 인프라스트럭쳐 없이 무선 노드로만 구성된 MANET은 높은 유연성을 제공하지만, 다양한 공격에 취약한 단점을 가지고 있다. 특히 모든 노드들이 패킷 포워딩을 수행해야 하기 때문에 DDoS 공격에 큰 취약점을 가지고 있다. 본 논문에서는 MANET에서 DDoS 공격의 피해를 완화시키고, DDoS 공격 발생시 공격자의 위치를 찾기 위한 패킷 전송 정보 관리 기법을 제안하였다. 본 논문에서는 DDoS 공격 대상을 보호하기 위하여 게이트웨이 노드를 이용하는 계층구조를 채택하였다. 소스 노드가 목적지 노드까지 경로 설정시 목적지 노드와 같은 클러스터내의 게이트웨이 노드가 반드시 포함되어야 하며, 이 게이트웨이 노드는 목적지 노드를 보호하는 기능을 수행한다. 본 논문에서 제안한 기법은 CUSUM 기법과 비교 실험하여 효율성을 확인하였고, 위치 추적에 사용할 정보 관리의 효율성을 평가하기 위해 클러스터 헤드의 메모리 사용량을 측정하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.410-413
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• 1993

Chamferless peg-in-hole process of the cylindrical type parts using force/torque sensor and vision sensor is analyzed and simulated in this paper. Peg-in-hole process is classified to the normal mode (only position error) and tilted mode(position and orientation error). The tilted mode is sub-classified to the small and the big tilted mode according to the relative orientation error. Since the big tilted node happened very rare, most papers dealt with only the normal or the small tilted mode. But the most errors of the peg-in-hole process happened in the big tilted mode. This problem is analyzed and simulated in this paper using the force/torque sensor and vision senor. In the normal mode, fuzzy logic is introduced to combine the data of the force/torque sensor and vision sensor. Also the whole processing algorithms and simulations are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권7호
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• pp.2286-2304
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• 2022

Blockchain is a distributed ledger that combines technologies such as cryptography, consensus mechanism, peer-to-peer transmission, and time stamping. The rapid development of blockchain has attracted attention from all walks of life, but storage scalability issues have hindered the application of blockchain. In this paper, a scalable blockchain storage model based on Distributed Hash Table (DHT) and the InterPlanetary File System (IPFS) was proposed. This paper introduces the current research status of the scalable blockchain storage model, as well as the basic principles of DHT and the InterPlanetary File System. The model construction and workflow are explained in detail. At the same time, the DHT network construction mechanism, block heat identification mechanism, new node initialization mechanism, and block data read and write mechanism in the model are described in detail. Experimental results show that this model can reduce the storage burden of nodes, and at the same time, the blockchain network can accommodate more local blocks under the same block height.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.3892-3912
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• 2021

The recent rapid growth of mobile network traffic places multi-access edge computing in an important position to reduce network load and improve network capacity and service quality. Contrasting with traditional mobile cloud computing, multi-access edge computing includes a base station cooperative cache layer and user cooperative cache layer. Selecting the most appropriate cache content according to actual needs and determining the most appropriate location to optimize the cache performance have emerged as serious issues in multi-access edge computing that must be solved urgently. For this reason, a cache placement algorithm based on comprehensive utility in big data multi-access edge computing (CPBCU) is proposed in this work. Firstly, the cache value generated by cache placement is calculated using the cache capacity, data popularity, and node replacement rate. Secondly, the cache placement problem is then modeled according to the cache value, data object acquisition, and replacement cost. The cache placement model is then transformed into a combinatorial optimization problem and the cache objects are placed on the appropriate data nodes using tabu search algorithm. Finally, to verify the feasibility and effectiveness of the algorithm, a multi-access edge computing experimental environment is built. Experimental results show that CPBCU provides a significant improvement in cache service rate, data response time, and replacement number compared with other cache placement algorithms.

• 정보과학회 논문지
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• 제44권1호
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• pp.84-94
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• 2017

최근 다양하고 방대한 양의 데이터를 처리하기 위해 빅데이터의 특성인 5V(Volume, Variety, Velocity, Veracity, Value) 중에서도 속도(Velocity)의 중요성이 강조되면서 대량의 데이터를 빠르고 정확하게 처리하는 기술인 실시간 스트림 처리(Real-time Stream processing)를 위해 많은 연구가 진행되고 있다. 본 논문에서는 실시간 빅데이터 처리를 위해 대표적인 실시간 객체 모델인 TMO(Time-triggered Message-triggered Object) 개념을 도입한 Squall 프레임워크를 제시하고, 단일 노드에서 동작하는 Squall 프레임워크와 그 동작들에 대해 기술한다. TMO는 작업을 수행할 때, 특정 조건에 대해 실시간으로 처리하는 비주기적인 처리방법과 일정 시간 간격동안 주기적인 처리를 지원하는 객체 모델이다. 따라서 Squall 프레임워크는 실시간 빅데이터의 실시간 이벤트 스트림 및 마이크로-배치 처리를 동시에 지원하고, 기존 아파치 스톰과 스파크 스트리밍 대비 상대적으로 우수한 성능을 제공한다. 하지만 Squall은 대부분의 프레임워크에서 제공되는 다중 노드에서의 실시간 분산처리를 위한 추가적인 개발이 필요하다. 결론적으로, TMO 모델의 장점은 실시간 빅데이터 처리시 기존 아파치의 스톰이나 스파크 스트리밍의 단점들을 극복할 수 있다. 이러한 TMO 모델은 실시간 빅데이터 처리에 있어 유용한 모델로서의 가능성을 가지고 있다.