• Title/Summary/Keyword: Hierarchical Network

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Modified LEACH Protocol improving the Time of Topology Reconfiguration in Container Environment (컨테이너 환경에서 토플로지 재구성 시간을 개선한 변형 LEACH 프로토콜)

  • Lee, Yang-Min;Yi, Ki-One;Kwark, Gwang-Hoon;Lee, Jae-Kee
    • The KIPS Transactions:PartC
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    • v.15C no.4
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    • pp.311-320
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    • 2008
  • In general, routing algorithms that were applied to ad-hoc networks are not suitable for the environment with many nodes over several thousands. To solve this problem, hierarchical management to these nodes and clustering-based protocols for the stable maintenance of topology are used. In this paper, we propose the clustering-based modified LEACH protocol that can applied to an environment which moves around metal containers within communication nodes. In proposed protocol, we implemented a module for detecting the movement of nodes on the clustering-based LEACH protocol and improved the defect of LEACH in an environment with movable nodes. And we showed the possibility of the effective communication by adjusting the configuration method of multi-hop. We also compared the proposed protocol with LEACH in four points of view, which are a gradual network composition time, a reconfiguration time of a topology, a success ratio of communication on an containers environment, and routing overheads. And to conclude, we verified that the proposed protocol is better than original LEACH protocol in the metal containers environment within communication of nodes.

A Judgment System for Intelligent Movement Using Soft Computing (소프트 컴퓨팅에 의한 지능형 주행 판단 시스템)

  • Choi, Woo-Kyung;Seo, Jae-Yong;Kim, Seong-Hyun;Yu, Sung-Wook;Jeon, Hong-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.5
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    • pp.544-549
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    • 2006
  • This research is to introduce about Judgment System for Intelligent Movement(JSIM) that can perform assistance work of human brain. JSIM can order autonomous command and also it can be directly controlled by user. This research assumes that control object is limited to Mobile Robot(MR) Mobile robot offers image and ultrasonic sensor information to user carrying JSIM and it performs guide to user. JSIM having PDA and Sensor-box controls velocity and direction of the mobile robot by soft-computing method that inputs user's command and information that is obtained to mobile robot. Also it controls mobile robot to achieve various movement. This paper introduces wearable JSIM that communicates with around devices and that can do intelligent judgment. To verify the possibility of the proposed system, in real environment, the simulation of control and application problem lot mobile robot will be introduced. Intelligent algorithm in the proposed system is generated by mixed hierarchical fuzzy and neural network.

Analysis on Nonstationarity in Mean Sea Level and Nonstationary Frequency Analysis based on Hierarchical Bayesian Model (해수면의 비정상성 검토 및 계층적 Bayesian 모형을 이용한 비정상성 빈도해석 기법 개발)

  • Kim, Yong Tak;Sumiya, Uranchimeg;Kwon, Hyun-Han
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.451-451
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    • 2015
  • 최근 1900년부터 1990년 사이 해수면은 매년 평균 1.2mm 상승했지만 1990년부터는 매년 평균 3mm씩 높아지고 있으며, 이에 1990년부터 현재까지 해수면 수위의 상승속도가 이전 90년 동안 측정된 수치보다 2.5배 빠르다는 연구결과가 발표되었다. 해수면 상승으로 인한 피해는 범람과 침식을 야기할 수 있으며 해일 및 폭풍으로 인한 피해를 증가시킴으로 물질적 피해와 인명 피해를 유발할 수 있다. 이러한 이유로 해수면 상승에 따른 과학적인 분석과 신뢰성 있는 전망을 통하여 해수면 상승에 따른 대응과 대비가 필요하다. 이에 본 연구에서는 비정상성 빈도해석 방법을 통하여 미래의 해수면 상승을 고려할 수 있는 비정상성 빈도해석 기법을 개발하였다. 본 연구에서는 극치사상을 추출하기 위해 국립해양조사원 (Korea Hydrographic and Oceanographic Administration, KHOA)에서 관리한 45개 조위관측소의 시 조위 자료를 이용하였다. 45개 조위관측소의 한 시간 단위 자료로부터 연최대 및 연평균 조위계열 (annual average and annual maximum sea level series)을 추출하였다. 본 연구에서는 한반도 해안을 동해안, 서해안, 남해안, 제주 권역으로 구분하고 빈도 해석의 신뢰성을 만족하기 위해 자료 구축기간이 20년 이상이며, 각 해안을 나타낼 수 있는 지점을 선정하였다. 비정상성 빈도해석은 Gumbel 극치분포를 적용하였으며, 계층적 Bayesian 기법을 결합하여 매개변수들에 대한 사후분포를 추정하였다. 본 연구에서는 대부분의 지점에서 비정상성 빈도해석 결과와 정상성 빈도해석 결과와 상당한 차이를 보여주고 있으며, 이는 주로 정상성 가정에 기인하는 문제점으로 판단된다. 향후 기후변화에 따른 연안지역의 홍수 및 사회기반시설의 위험도를 평가하기 위해서는 비정상성을 고려한 빈도해석 절차의 수립과 적용이 필요할 것으로 판단된다.

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Constructions of Totalitarian Subjectivity in Joseph Conrad's Heart of Darkness (죠셉 콘래드의 『어둠의 속』에 나타난 전체주의적 주체성의 형성)

  • Koo, Seung-pon
    • Cross-Cultural Studies
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    • v.45
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    • pp.479-496
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    • 2016
  • The aim of this essay was to investigate Marlow's desire for constructing enlightenment subject of knowledge and power sustained by the collusion of imperialism and patriarchy in Joseph Conrad's Heart of Darkness. Marlow's narrative, based on his journey up the river in Africa to retrieve Kurtz, attempts to conceptualize himself as the subject of the enlightenment reason and rationality. In the novella, collusive network of ideologies of empire and gender contributes to the making of a Western Enlightenment subject. Marlow eulogizes himself for realizing the harsh realities of imperialism, political domination and economic exploitation of the natives in Africa. However, Marlow is a colonial subject who has been ruled by the hierarchical system of thought in the Western logocentrism. He is not aware that his narrative has already been infiltrated by the ideological discourse of the totalitarian enlightenment. His narrative in effect is not a self-congratulatory testimony to truth and realities but a narcissistic and self-defeating document. Marlow unconsciously employs the totalitarian ideologies of empire and gender in order to relegate the African natives to the inhuman existence and to consign women to the sphere of illusion.

Sea Ice Type Classification with Optical Remote Sensing Data (광학영상에서의 해빙종류 분류 연구)

  • Chi, Junhwa;Kim, Hyun-cheol
    • Korean Journal of Remote Sensing
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    • v.34 no.6_2
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    • pp.1239-1249
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    • 2018
  • Optical remote sensing sensors provide visually more familiar images than radar images. However, it is difficult to discriminate sea ice types in optical images using spectral information based machine learning algorithms. This study addresses two topics. First, we propose a semantic segmentation which is a part of the state-of-the-art deep learning algorithms to identify ice types by learning hierarchical and spatial features of sea ice. Second, we propose a new approach by combining of semi-supervised and active learning to obtain accurate and meaningful labels from unlabeled or unseen images to improve the performance of supervised classification for multiple images. Therefore, we successfully added new labels from unlabeled data to automatically update the semantic segmentation model. This should be noted that an operational system to generate ice type products from optical remote sensing data may be possible in the near future.

A Bibliometric Approach for Department-Level Disciplinary Analysis and Science Mapping of Research Output Using Multiple Classification Schemes

  • Gautam, Pitambar
    • Journal of Contemporary Eastern Asia
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    • v.18 no.1
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    • pp.7-29
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    • 2019
  • This study describes an approach for comparative bibliometric analysis of scientific publications related to (i) individual or several departments comprising a university, and (ii) broader integrated subject areas using multiple disciplinary schemes. It uses a custom dataset of scientific publications (ca. 15,000 articles and reviews, published during 2009-2013, and recorded in the Web of Science Core Collections) with author affiliations to the research departments, dedicated to science, technology, engineering, mathematics, and medicine (STEMM), of a comprehensive university. The dataset was subjected, at first, to the department level and discipline level analyses using the newly available KAKEN-L3 classification (based on MEXT/JSPS Grants-in-Aid system), hierarchical clustering, correspondence analysis to decipher the major departmental and disciplinary clusters, and visualization of the department-discipline relationships using two-dimensional stacked bar diagrams. The next step involved the creation of subsets covering integrated subject areas and a comparative analysis of departmental contributions to a specific area (medical, health and life science) using several disciplinary schemes: Essential Science Indicators (ESI) 22 research fields, SCOPUS 27 subject areas, OECD Frascati 38 subordinate research fields, and KAKEN-L3 66 subject categories. To illustrate the effective use of the science mapping techniques, the same subset for medical, health and life science area was subjected to network analyses for co-occurrences of keywords, bibliographic coupling of the publication sources, and co-citation of sources in the reference lists. The science mapping approach demonstrates the ways to extract information on the prolific research themes, the most frequently used journals for publishing research findings, and the knowledge base underlying the research activities covered by the publications concerned.

Modified Back-Off Algorithm to Improve Fairness for Slotted ALOHA Sensor Networks (슬롯화된 ALOHA 센서 네트워크에서 공평성 향상을 위한 변형된 백오프 알고리즘)

  • Lee, Jong-Kwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.5
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    • pp.581-588
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    • 2019
  • In this paper, I propose an modified back-off algorithm to improve the fairness for slotted ALOHA sensor networks. In hierarchical networks, the performance degradation of a specific node can cause degradation of the overall network performance in case the data transmitted by lower nodes is needed to be synthesized and processed by an upper node. Therefore it is important to ensure the fairness of transmission performance to all nodes. The proposed scheme choose a back-off time of a node considering the previous transmission results as well as the current transmission result. Moreover a node that failed to transmit consecutively is given gradually shorter back-off time but a node that is success to transmit consecutively is given gradually longer back-off time. Through simulations, I compare and analyze the performance of the proposed scheme with the binary exponential back-off algorithm(BEB). The results show that the proposed scheme reduces the throughput slightly compared to BEB but improves the fairness significantly.

A Bio-inspired Hybrid Cross-Layer Routing Protocol for Energy Preservation in WSN-Assisted IoT

  • Tandon, Aditya;Kumar, Pramod;Rishiwal, Vinay;Yadav, Mano;Yadav, Preeti
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1317-1341
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    • 2021
  • Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.

A operation scheme to the power consumption of base station in wireless networks (무선망에서 기지국의 전력소모에 대한 운영 방안)

  • Park, Sangjoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.2
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    • pp.285-289
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    • 2020
  • The configuration of hierarchical wireless networks is provided to support diverse network environments. In the base station, two system state can be basically considered for the operation management so that the state transition may be occurred between active and sleep modes. Hence, to reduce energy consumption the system operation management of the low power should be considered to the base station system. In this paper we consider the analytical model of Discontinuous Reception (DRX) to investigate the system management. We provide the analysis scheme of base station system by the DRX model, and the low power factor would be investigated for the energy consumption. We also use the finite-state Markov system model that in a system state period the wireless resource request and the operation of service call arrival interval is considered to numerically analyze the performance of energy saving operations of base station.

A Blockchain-based User-centric Role Based Access Control Mechanism (블록체인 기반의 사용자 중심 역할기반 접근제어 기법 연구)

  • Lee, YongJoo;Woo, SungHee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.7
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    • pp.1060-1070
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    • 2022
  • With the development of information technology, the size of the system has become larger and diversified, and the existing role-based access control has faced limitations. Blockchain technology is being used in various fields by presenting new solutions to existing security vulnerabilities. This paper suggests efficient role-based access control in a blockchain where the required gas and processing time vary depending on the access frequency and capacity of the storage. The proposed method redefines the role of reusable units, introduces a hierarchical structure that can efficiently reflect dynamic states to enhance efficiency and scalability, and includes user-centered authentication functions to enable cryptocurrency linkage. The proposed model was theoretically verified using Markov chain, implemented in Ethereum private network, and compared experiments on representative functions were conducted to verify the time and gas efficiency required for user addition and transaction registration. Based on this in the future, structural expansion and experiments are required in consideration of exception situations.