• Title/Summary/Keyword: Computing Resource

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Structural Optimization based on Equivalent Static Load for Structure under Dynamic Load (동하중을 받는 구조물의 등가정하중 기반 구조최적화 연구)

  • Kim, Hyun Gi;Kim, Eui young;Cho, Maenghyo
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2013.10a
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    • pp.236-240
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    • 2013
  • Due to difficulty of considering dynamic load in side of a computer resource and computing time, it is common that external load is assumed as ideal static load. However, structural analysis under static load cannot guarantee the safety of structural design. Recently, the systematic method to construct equivalent static load from the given dynamic load has been proposed. Previous study has calculated equivalent static load through the optimization procedure under displacement constraints. And previously reported works to distribute equivalent static load were based on ad hoc methods. However, it is appropriate to take into account the stress constraint for the safety design. Moreover, the improper selection of loading position may results in unreliable structural design. The present study proposes the methodology to optimize an equivalent static which distributed on the primary DOFs, DOFs of the constraint elements, DOF of an external load as positions. In conclusion, the reliability of proposed method is demonstrated through a global optimization.

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A Survey on Transport Protocols for Wireless Multimedia Sensor Networks

  • Costa, Daniel G.;Guedes, Luiz Affonso
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.1
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    • pp.241-269
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    • 2012
  • Wireless networks composed of multimedia-enabled resource-constrained sensor nodes have enriched a large set of monitoring sensing applications. In such communication scenario, however, new challenges in data transmission and energy-efficiency have arisen due to the stringent requirements of those sensor networks. Generally, congested nodes may deplete the energy of the active congested paths toward the sink and incur in undesired communication delay and packet dropping, while bit errors during transmission may negatively impact the end-to-end quality of the received data. Many approaches have been proposed to face congestion and provide reliable communications in wireless sensor networks, usually employing some transport protocol that address one or both of these issues. Nevertheless, due to the unique characteristics of multimedia-based wireless sensor networks, notably minimum bandwidth demand, bounded delay and reduced energy consumption requirement, communication protocols from traditional scalar wireless sensor networks are not suitable for multimedia sensor networks. In the last decade, such requirements have fostered research in adapting existing protocols or proposing new protocols from scratch. We survey the state of the art of transport protocols for wireless multimedia sensor networks, addressing the recent developments and proposed strategies for congestion control and loss recovery. Future research directions are also discussed, outlining the remaining challenges and promising investigation areas.

Elliptic Curve Cryptography Algorithms for IC Card (IC 카드용 타원곡선 암호 알고리즘)

  • 이택희;서창호;김영철;이태훈;윤보현
    • Journal of KIISE:Computing Practices and Letters
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    • v.10 no.4
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    • pp.319-327
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    • 2004
  • This paper describes implementations and test results of Elliptic Curve Cryptography (ECC) and Elliptic Curve KCDSA(ECKCDSA) algorithms based on Java card. 163-Bit ECC guarantees as secure as 1024-Bit Rivest-Shamir-Adleman (RSA) public key algorithm, which has been frequently used until now. According to our test results, 163-bit ECC processing time is about five times fast compared with 1024-bit RSA and amount of resource usages of ECC is smaller than RSA. Therefore, ECC is more appropriate for use on secure devices such as smart cards and wireless devices with constrained computational power consumption and small memory resources.

Edge Computing-Based Unmanned Market Case Study: Maximizing Resource Distribution (엣지 컴퓨팅 기반 무인 마켓 사례 연구: 자원 분배 효율성 극대화)

  • Park, Ji-Hoon;Ryu, Hyeong-Oh;Kim, KyoungRul;Kim, Saehwa
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.10a
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    • pp.221-224
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    • 2019
  • 본 논문에서는 엣지 컴퓨팅을 무인 마켓에 도입하여 엣지 컴퓨팅의 효율성을 확인하고, 로컬 네트워크의 효율적인 대역폭 할당을 위한 두 가지 방법을 제안한다. 무인 마켓과 같이 엄청난 양의 데이터를 필요로 하고 만들어내는 서비스에서는 데이터들을 클라우드로 전송하여 소비자가 불편함을 느끼지 못하도록 빠르게 처리하는 것은 불가능에 가깝다. 그래서 우리는 Amazon Go 를 벤치마킹한 무인 마켓에 엣지 컴퓨팅을 도입하여 이를 구현한다. 그리고 구현한 시스템에서 엣지 컴퓨팅 외에 클라우드 컴퓨팅, 모바일 장치를 적용하여 처리할 때의 응답 시간을 분석하여 엣지 컴퓨팅의 높은 성능을 확인한다. 또한, 구현한 무인 마켓에서 데이터 전송의 효율성을 더욱 높이기 위해 카메라 단위와 매대 단위의 대역폭 할당 기법을 제안한다. 카메라 단위로는 모션 인식기술을 활용하여 움직임이 감지될 때만 각 이미지 프로세스에서 요구되는 고해상도로 송신하는 기법을 제안한다. 매대 단위로는 네트워크에서 수용 가능한 대역폭 임계치에 도달하지 못하게 하기 위해 매대 별 우선순위에 따른 대역폭 할당 스케줄링 기법을 제안한다. 그 결과로 평균 소모대역폭과 최대 소모대역폭을 비교하여 제안한 두 가지 기법이 기존의 방법에 비해 성능을 향상시키는 것을 보인다.

Analysis of Global Trends and Issues of Cognitive Radio (Cognitive Radio 연구의 국내외 동향과 이슈 분석)

  • Moon, Sangook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.969-972
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    • 2009
  • With the advent of the era of ubiquitous computing, the number of wireless communication devices has been exponentially increasing, which phenomenon requires for the preparation for the upcoming shortage of frequency resource. Recently, in consequence, the concept of Cognitive Radio (CR) was introduced in which the wireless nodes periodically recognize and learn the external conditions of communication including the usage of the frequency spectrum. It is essential to assure sufficient range of frequency to satisfy the users of the increasing wireless network devices. However, since not only the frequency band for wireless communication is finite, but most part of them had already been assigned for the primary users of the wireless network service, it is very difficult to ensure the band of frequency for additional communication service. In this contribution, we analyze and describe the issues of designing and implementation of CR networks.

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Review of researches on coupled system and CFD codes

  • Long, Jianping;Zhang, Bin;Yang, Bao-Wen;Wang, Sipeng
    • Nuclear Engineering and Technology
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    • v.53 no.9
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    • pp.2775-2787
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    • 2021
  • At present, most of the widely used system codes for nuclear safety analysis are one-dimensional, which cannot effectively simulate the flow field of the reactor core or other structures. This is true even for the system codes containing three-dimensional modules with limited three-dimensional simulation function such as RELAP-3D. In contrast, the computational fluid dynamics (CFD) codes excel at providing a detailed three-dimensional flow field of the reactor core or other components; however, the computational domain is relatively small and results in the very high computing resource consuming. Therefore, the development of coupling codes, which can make comprehensive use of the advantages of system and CFD codes, has become a research focus. In this paper, a review focus on the researches of coupled CFD and thermal-hydraulic system codes was carried out, which summarized the method of coupling, the data transfer processing between CFD and system codes, and the verification and validation (V&V) of coupled codes. Furthermore, a series of problems associated with the coupling procedure have been identified, which provide the general direction for the development and V&V efforts of coupled codes.

Research Trends Analysis of Big Data: Focused on the Topic Modeling (빅데이터 연구동향 분석: 토픽 모델링을 중심으로)

  • Park, Jongsoon;Kim, Changsik
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.1
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    • pp.1-7
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    • 2019
  • The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

Increase Resource Efficiency by Leveraging Cloud Trade in Multi-Gateway (다중 게이트웨이 환경에서의 클라우드 트레이드를 활용한 자원 효율성 증대)

  • Lee, Tae-Ho;Kim, Dong-Hyun;Lee, Byung-Jun;Kim, Kyung-Tae;Youn, Hee-Yong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.01a
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    • pp.153-154
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    • 2019
  • 본 논문에서는 사물인터넷(Internet of Things, IoT)에 적용되어 사용될 수 있는 다중 게이트웨이 환경에서 각 게이트웨이의 자원 상황에 따라 종단 노드를 클라우드 단으로 직접 트레이드하여 처리함으로서 게이트웨이의 자원 소모를 줄이고 높은 처리량을 요구하는 종단 노드를 빠르게 처리 가능한 기법을 제안한다. 본 논문에서는 해당 기법의 효율성 입증을 위하여 클라우드 컴퓨팅이라는 대규모 환경을 가정하여 실험을 진행하였으며, 해당 실험의 결과에 따르면 높은 처리량을 요구하는 종단 노드를 클라우드 단에 트레이드하여 직접 처리함으로서 클라우드 단 하부의 다중 게이트웨이의 자원 소모율 감소 및 데이터 처리 속도가 증대 되었음을 확인할 수 있다.

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Implementation of a Raspberry-Pi-Sensor Network (라즈베리파이 센서 네트워크 구현)

  • Moon, Sangook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.915-916
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    • 2014
  • With the upcoming era of internet of things, the study of sensor network has been paid attention. Raspberry pi is a tiny versatile computer system which is able to act as a sensor node in hadoop cluster network. In this paper, we deployed 5 Raspberry pi's to construct an experimental testbed of hadoop sensor network with 5-node map-reduce hadoop software framework. We compared and analyzed the network architecture in terms of efficiency, resource management, and throughput using various parameters. We used a learning machine with support vector machine as test workload. In our experiments, Raspberry pi fulfilled the role of distributed computing sensor node in the sensor network.

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Design and Implementation of Incremental Learning Technology for Big Data Mining

  • Min, Byung-Won;Oh, Yong-Sun
    • International Journal of Contents
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    • v.15 no.3
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    • pp.32-38
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    • 2019
  • We usually suffer from difficulties in treating or managing Big Data generated from various digital media and/or sensors using traditional mining techniques. Additionally, there are many problems relative to the lack of memory and the burden of the learning curve, etc. in an increasing capacity of large volumes of text when new data are continuously accumulated because we ineffectively analyze total data including data previously analyzed and collected. In this paper, we propose a general-purpose classifier and its structure to solve these problems. We depart from the current feature-reduction methods and introduce a new scheme that only adopts changed elements when new features are partially accumulated in this free-style learning environment. The incremental learning module built from a gradually progressive formation learns only changed parts of data without any re-processing of current accumulations while traditional methods re-learn total data for every adding or changing of data. Additionally, users can freely merge new data with previous data throughout the resource management procedure whenever re-learning is needed. At the end of this paper, we confirm a good performance of this method in data processing based on the Big Data environment throughout an analysis because of its learning efficiency. Also, comparing this algorithm with those of NB and SVM, we can achieve an accuracy of approximately 95% in all three models. We expect that our method will be a viable substitute for high performance and accuracy relative to large computing systems for Big Data analysis using a PC cluster environment.