• 제목/요약/키워드: Edge networks

검색결과 341건 처리시간 0.029초

Edge Router Selection and Traffic Engineering in LISP-Capable Networks

  • Li, Ke;Wang, Sheng;Wang, Xiong
    • Journal of Communications and Networks
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    • 제13권6호
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    • pp.612-620
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    • 2011
  • Recently, one of the problems with the Internet is the issue of scalability. To this end, locator/identifier separation protocol (LISP), which separates end-system identifiers and routing locators, has been proposed as a solution. In the LISP deployed network, the ingress and egress nodes of inter-AS traffic is determined by edge router selection (ERS) and endpoint identifier-routing locator mapping assignment (ERMA). In this paper, joint optimizations of ERS and ERMA for stub networks with and without predetermined link weights are studied and the mixed integer linear programming (MILP) formulations for the problems are given. To make the problem with optimizable link weights tractable, a revised local search algorithm is also proposed. Simulation results show that joint optimization of ERS and ERMA enables better network performance.

이항트리에서 S-에지번호 매김 (The S-Edge Numbering on Binomial trees)

  • 김용석
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 하계종합학술대회 논문집(1)
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    • pp.167-170
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    • 2004
  • We present a novel graph labeling problem called S-edge labeling. The constraint in this labeling is placed on the allowable edge label which is the difference between the labels of endvertices of an edge. Each edge label should be ${ a_n / a_n = 4 a_{n-l}+l,\;a_{n-1}=0}$. We show that every binomial tree is possible S-edge labeling by giving labeling schems to them. The labelings on the binomial trees are applied to their embedings into interconnection networks.

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Cooperative Content Caching and Distribution in Dense Networks

  • Kabir, Asif
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권11호
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    • pp.5323-5343
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    • 2018
  • Mobile applications and social networks tend to enhance the need for high-quality content access. To address the rapid growing demand for data services in mobile networks, it is necessary to develop efficient content caching and distribution techniques, aiming at significantly reduction of redundant content transmission and thus improve content delivery efficiency. In this article, we develop optimal cooperative content cache and distribution policy, where a geographical cluster model is designed for content retrieval across the collaborative small cell base stations (SBSs) and replacement of cache framework. Furthermore, we divide the SBS storage space into two equal parts: the first is local, the other is global content cache. We propose an algorithm to minimize the content caching delay, transmission cost and backhaul bottleneck at the edge of networks. Simulation results indicates that the proposed neighbor SBSs cooperative caching scheme brings a substantial improvement regarding content availability and cache storage capacity at the edge of networks in comparison with the current conventional cache placement approaches.

소프트웨어 정의 모바일 에지 차량 네트워크(SDMEVN)의 센싱 데이터 수집 전략 (A Sensing Data Collection Strategy in Software-Defined Mobile-Edge Vehicular Networks (SDMEVN))

  • 라이오넬;장종욱
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2018년도 추계학술대회
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    • pp.62-65
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    • 2018
  • This paper comes out with the study on sensing data collection strategy in a Software-Defined Mobile Edge vehicular networking. The two cooperative data dissemination are Direct Vehicular cloud mode and edge cell trajectory prediction decision mode. In direct vehicular cloud, the vehicle observe its neighboring vehicles and sets up vehicular cloud for cooperative sensing data collection, the data collection output can be transmitted from vehicles participating in the cooperative sensing data collection computation to the vehicle on which the sensing data collection request originate through V2V communication. The vehicle on which computation originate will reassemble the computation out-put and send to the closest RSU. The SDMEVN (Software Defined Mobile Edge Vehicular Network) Controller determines how much effort the sensing data collection request requires and calculates the number of RSUs required to support coverage of one RSU to the other. We set up a simulation scenario based on realistic traffic and communication features and demonstrate the scalability of the proposed solution.

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An Efficient Algorithm for Finding the k-edge Survivability in Ring Networks

  • Myung, Young-Soo
    • Management Science and Financial Engineering
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    • 제16권3호
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    • pp.85-93
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    • 2010
  • Given an undirected network with a set of source-sink pairs, we are assumed to get a benefit if a pair of source and sink nodes are connected. The k-edge survivability of a network is defined as the total benefit secured after arbitrarily selected k edges are destroyed. The problem of computing k-edge survivability is known to be NP-hard and has applications of evaluating the survivability or vulnerability of a network. In this paper, we consider the k-edge survivability problem restricted to ring networks and develop an algorithm to solve it in O($n^3$|K|) time where n is the number of nodes and K is the set of source-sink pairs.

Face Detection Based on Thick Feature Edges and Neural Networks

  • Lee, Young-Sook;Kim, Young-Bong
    • 한국멀티미디어학회논문지
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    • 제7권12호
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    • pp.1692-1699
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    • 2004
  • Many researchers have developed various techniques for detection of human faces in ordinary still images. Face detection is the first imperative step of human face recognition systems. The two main problems of human face detection are how to cutoff the running time and how to reduce the number of false positives. In this paper, we present frontal and near-frontal face detection algorithm in still gray images using a thick edge image and neural network. We have devised a new filter that gets the thick edge image. Our overall scheme for face detection consists of two main phases. In the first phase we describe how to create the thick edge image using the filter and search for face candidates using a whole face detector. It is very helpful in removing plenty of windows with non-faces. The second phase verifies for detecting human faces using component-based eye detectors and the whole face detector. The experimental results show that our algorithm can reduce the running time and the number of false positives.

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Edge Detection Method Based on Neural Networks for COMS MI Images

  • Lee, Jin-Ho;Park, Eun-Bin;Woo, Sun-Hee
    • Journal of Astronomy and Space Sciences
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    • 제33권4호
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    • pp.313-318
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    • 2016
  • Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

MPOA/MPLS 연동망의 심리스 연결을 위한 에지 라우터 구조 (Structure of Edge Routers for Seamless Connection in MPOA/MPLS Interworked Networks)

  • 김동호;이숭희
    • 대한전자공학회논문지TC
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    • 제38권10호
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    • pp.10-17
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    • 2001
  • 고속 인터넷 서비스 제공을 위한 서로 다른 망 기술 간 연동 방안의 마련이 요구되고 있다. 특히 연동 지점 노드에서의 동작구조는 전송효율에 큰 영향을 미칠 수 있다. 본 논문은 MPOA 망과 MPLS 망의 연동 부담을 최소화 하기 위한 심리스 연결 방안과 연동지점에 위치한 에지 라우터의 연동 기능을 제시한다. 두 망은 ATM을 기반으로 하거나 적용 할 수 있으므로 ATM 심리스 연결이 가능한 연동 방안을 제시하고 심리스 연결을 고려하지 않은 연동 방안과 비교한다. 제시된 두 가지 연동 방안들을 컴퓨터 시뮬레이션하여 전송 지연 결과를 분석하고, MPLS 망의 에지 라우터에 필요한 연동 기능과 동작을 기술한다.

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베이지안 망 연결 구조에 대한 데이터 군집별 기여도의 정량화 방법에 대한 연구 (Quantitative Annotation of Edges, in Bayesian Networks with Condition-Specific Data)

  • 정성원;이도헌;이광형
    • 한국지능시스템학회논문지
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    • 제17권3호
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    • pp.316-321
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    • 2007
  • 본 연구에서는 베이지안 망 구조 학습에서, 학습 데이터의 특정 부분집합이 학습된 망의 각 연결 구조(edge)의 형성에 기여하는 정도를 정량화하는 방법을 제안한다. 생물학 정보의 분석 등에 베이지안 망 학습을 이용하는 경우, 제안된 방법은 망의 각 연결 구조의 형성에 특정 군집 데이터가 기여하는 정도의 정량화가 가능하다. 제안된 방법의 유효성을 보이기 위해, 벤치마크 베이지안 망을 이용하여 제안된 방법이 망 연결 구조에 대한 데이터 군집별 기여도를 효과적으로 정량화 할 수 있음을 보인다.

Future Trends of IoT, 5G Mobile Networks, and AI: Challenges, Opportunities, and Solutions

  • Park, Ji Su;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • 제16권4호
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    • pp.743-749
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    • 2020
  • Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edge-server. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.