Adjacent Node

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Moshe Zukerman - One of the best experts on this subject based on the ideXlab platform.

  • Heuristic algorithms for multicast traffic grooming in WDM mesh networks
    2011 8th International Conference on Information Communications & Signal Processing, 2011
    Co-Authors: Wen-de Zhong, Sanjay Kumar Bose, Moshe Zukerman
    Abstract:

    Multicast traffic grooming is used to multiplex or groom multiple low bandwidth multicast connections into a high bandwidth wavelength channel or light-tree to increase the utilization of wavelength. However, multicast traffic grooming is NP-hard problem. Thus, we propose two heuristic algorithms with polynomial complexities, called Adjacent Node Component based Grooming for Throughput (ANCG-T) and Dividable Light-Tree Grooming (DLTG) algorithm, to achieve scalable design for realistic networks in realistic networks. ANCG-T algorithm is to divide light-tree into sub-light-trees which are within two optical hops, to increase sharing of resources. DLTG algorithm is based on grooming traffic to light-trees and also on dividing a light-tree to sub-light-trees and then grooming traffic to these sub-light-trees to improve resource utilization. Simulations show that both the algorithms have throughput performances which are very close to optimal results, and that the DLTG algorithm can achieve better network throughput than the ANCG-T algorithm.

  • Dynamic Sub-Light-Tree Based Traffic Grooming for Multicast in WDM Networks
    2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010
    Co-Authors: Wen-de Zhong, Sanjay Kumar Bose, Moshe Zukerman
    Abstract:

    This paper proposes a multicast traffic grooming scheme for efficient resource utilization in wavelength- division multiplexing (WDM) mesh networks. This Light-Tree Division -Adjacent Node Component based Grooming scheme (LTD-ANCG) is based on the idea of dividing a light-tree into smaller sub-light-trees. It improves the efficiency of resource utilization and lowers the optical- electronic-optical (OEO) conversion overhead. We use computer simulations to evaluate the performance of the scheme. Our simulations demonstrate that compared with existing algorithms, the new scheme significantly reduces the request blocking probability but can be implemented with very reasonable electronic processing.

Wen-de Zhong - One of the best experts on this subject based on the ideXlab platform.

  • Heuristic algorithms for multicast traffic grooming in WDM mesh networks
    2011 8th International Conference on Information Communications & Signal Processing, 2011
    Co-Authors: Wen-de Zhong, Sanjay Kumar Bose, Moshe Zukerman
    Abstract:

    Multicast traffic grooming is used to multiplex or groom multiple low bandwidth multicast connections into a high bandwidth wavelength channel or light-tree to increase the utilization of wavelength. However, multicast traffic grooming is NP-hard problem. Thus, we propose two heuristic algorithms with polynomial complexities, called Adjacent Node Component based Grooming for Throughput (ANCG-T) and Dividable Light-Tree Grooming (DLTG) algorithm, to achieve scalable design for realistic networks in realistic networks. ANCG-T algorithm is to divide light-tree into sub-light-trees which are within two optical hops, to increase sharing of resources. DLTG algorithm is based on grooming traffic to light-trees and also on dividing a light-tree to sub-light-trees and then grooming traffic to these sub-light-trees to improve resource utilization. Simulations show that both the algorithms have throughput performances which are very close to optimal results, and that the DLTG algorithm can achieve better network throughput than the ANCG-T algorithm.

  • Dynamic Sub-Light-Tree Based Traffic Grooming for Multicast in WDM Networks
    2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010
    Co-Authors: Wen-de Zhong, Sanjay Kumar Bose, Moshe Zukerman
    Abstract:

    This paper proposes a multicast traffic grooming scheme for efficient resource utilization in wavelength- division multiplexing (WDM) mesh networks. This Light-Tree Division -Adjacent Node Component based Grooming scheme (LTD-ANCG) is based on the idea of dividing a light-tree into smaller sub-light-trees. It improves the efficiency of resource utilization and lowers the optical- electronic-optical (OEO) conversion overhead. We use computer simulations to evaluate the performance of the scheme. Our simulations demonstrate that compared with existing algorithms, the new scheme significantly reduces the request blocking probability but can be implemented with very reasonable electronic processing.

Xue-zhang Liang - One of the best experts on this subject based on the ideXlab platform.

  • FCST - Research on Enhancing Human Finger Vein Pattern Characteristics Based on Adjacent Node Threshold Image Method
    2010 Fifth International Conference on Frontier of Computer Science and Technology, 2010
    Co-Authors: Xue-zhang Liang
    Abstract:

    An image of a finger captured under infrared light contains not only the vein pattern but also irregular shading produced by the various thicknesses of the finger bones and muscles. In this paper, we propose a new method to enhance the contrast of the finger vein image. It consists of five parts: wavelet denoising, normalization, Adjacent Node threshold image method, eliminate black block and burr, thinning. Firstly, we perform stationary wavelet decomposition and transform the image into four frequency bands and design different denoising methods to different frequency bands. Then, we nomalizate efficitive gray value range of finger-vein image to [0, 255]. And then, the binary image is got by Adjacent Node threshold image method. In the next, small blocks and burr are eliminated basing on the area size and by median filter algorithm separately. Finally, we obtain the skeleton by the quick thinning algorithm. The experiments show that the proposed method can properly enhance the contrast of the finger-vein image and make the skeleton express geometric structure of the hand vein image better.

  • Research on Enhancing Human Finger Vein Pattern Characteristics Based on Adjacent Node Threshold Image Method
    2010 Fifth International Conference on Frontier of Computer Science and Technology, 2010
    Co-Authors: Xue-zhang Liang
    Abstract:

    An image of a finger captured under infrared light contains not only the vein pattern but also irregular shading produced by the various thicknesses of the finger bones and muscles. In this paper, we propose a new method to enhance the contrast of the finger vein image. It consists of five parts: wavelet denoising, normalization, Adjacent Node threshold image method, eliminate black block and burr, thinning. Firstly, we perform stationary wavelet decomposition and transform the image into four frequency bands and design different denoising methods to different frequency bands. Then, we nomalizate efficitive gray value range of finger-vein image to [0, 255]. And then, the binary image is got by Adjacent Node threshold image method. In the next, small blocks and burr are eliminated basing on the area size and by median filter algorithm separately. Finally, we obtain the skeleton by the quick thinning algorithm. The experiments show that the proposed method can properly enhance the contrast of the finger-vein image and make the skeleton express geometric structure of the hand vein image better.

Jihad El-sana - One of the best experts on this subject based on the ideXlab platform.

  • ICFHR - Word Spotting Using Radial Descriptor Graph
    2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2016
    Co-Authors: Majeed Kassis, Jihad El-sana
    Abstract:

    In this paper we present, the Radial Descriptor Graph, a novel approach to compare pictorial representation of handwritten text, which is based on the radial descriptor. To build a radial descriptor graph, we compute the radial descriptor and generate feature points. These points are the Nodes of the graph, and each Adjacent points are connected to its Adjacent Node to form a planar graph. Then we iteratively reduce the edges of the graph, by merging Adjacent Nodes, to form a multilevel hierarchical representation of the graph. To compare two pictorial representations, we measure the distance between their correspondence planar graphs, after calculating the dominant signal for each Node. The graph matching is based on optimizing the function that takes into account the distance between the feature points and the structure of the graphs. The distance between two radial descriptors is computed by measuring the difference between their corresponding dominant signals. We have tested our approach on three different datasets and obtained encouraging results.

  • Word Spotting Using Radial Descriptor Graph
    2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2016
    Co-Authors: Majeed Kassis, Jihad El-sana
    Abstract:

    In this paper we present, the Radial Descriptor Graph, a novel approach to compare pictorial representation of handwritten text, which is based on the radial descriptor. To build a radial descriptor graph, we compute the radial descriptor and generate feature points. These points are the Nodes of the graph, and each Adjacent points are connected to its Adjacent Node to form a planar graph. Then we iteratively reduce the edges of the graph, by merging Adjacent Nodes, to form a multilevel hierarchical representation of the graph. To compare two pictorial representations, we measure the distance between their correspondence planar graphs, after calculating the dominant signal for each Node. The graph matching is based on optimizing the function that takes into account the distance between the feature points and the structure of the graphs. The distance between two radial descriptors is computed by measuring the difference between their corresponding dominant signals. We have tested our approach on three different datasets and obtained encouraging results.

Y. Tamura - One of the best experts on this subject based on the ideXlab platform.

  • Tree formation multi-robot system for victim search in a devastated indoor space
    2004 IEEE RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566), 2004
    Co-Authors: Y. Matsuo, Y. Tamura
    Abstract:

    A new scheme called "S3 RoboNet: self spreading search robot network" is proposed and described, which employs a multi-robot system to search for victims in a devastated indoor space such as inside of a collapsed building right after a large earthquake. In this scheme, numerous mobile robot agents form and expand a virtual network autonomously, in which the distance between every pair of Adjacent Node agents are kept within a limit so that they can keep locating each other. The network virtually composes a topological search map by itself and generates an artificial velocity potential in order to drive free agents towards unexplored regions and to make Node agents spread links among them as far as possible. Thereby, the network spreads itself only by adding a new free or a Node agent at the root of the tree located at the entrance of the space to be searched. The concepts and the algorithms of the present scheme are described and its feasibility and essential performance are analyzed by simulation, and both effectiveness and current problems are discussed.