• Title/Summary/Keyword: network tools

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A Study on Efficient Network Topology Visualization using Node Centrality (노드 중심성을 이용한 효율적 네트워크 토폴로지 시각화 연구)

  • Chang, Beom-Hwan;Ryu, Jemin;Kwon, Koohyung
    • Convergence Security Journal
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    • v.21 no.2
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    • pp.47-56
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    • 2021
  • Network topology visualization has been studied a lot since the past and developed with many tools. The network topology has strength in understanding the overall structure of a network physically and is useful for understanding data flow between nodes logically. Although there are existing tools, not many can be utilized efficiently while using the general network node data structure and express the topology similar to the actual network structure. In this paper, we propose an efficient method to visualize topology using only connection information of network nodes. The method finds the central node by using the centrality, the influence of nodes in the network, and visualizes the topology by dynamically segmenting all nodes and placing network nodes in 3D space using the weight of the child node. It is a straightforward method, yet it effectively visualizes in the form of an actual network structure.

A Study on Traffic Volume Prediction for e-Commerce Systems (전자상거래 시스템의 트래픽량 예측에 관한 연구)

  • Kim, Jeong-Su
    • The KIPS Transactions:PartC
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    • v.18C no.1
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    • pp.31-44
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    • 2011
  • The applicability of network-based computing depends on the availability of the underlying network bandwidth. Such a growing gap between the capacity of the backbone network and the end users' needs results in a serious bottleneck of the access network in between. As a result, ISP incurs disadvantages in their business. If this situation is known to ISP in advance, or if ISP is able to predict traffic volume end-to-end link high-load zone, ISP and end users would be able to decrease the gap for ISP service quality. In this paper, simulation tools, such as ACE, ADM, and Flow Analysis, were used to be able to perceive traffic volume prediction and end-to-end link high-load zone. In using these simulation tools, we were able to estimate sequential transaction in real-network for e-Commerce. We also imported virtual network environment estimated network data, and create background traffic. In a virtual network environment like this, we were able to find out simulation results for traffic volume prediction and end-to-end link high-load zone according to the increase in the number of users based on virtual network environment.

A Study on the Design of WDM Network using Traffic Demand Estimation Modeling (트래픽수요예측모델링을 통한 WDM네트워크 설계에 관한 연구)

  • 오호일;송재연;김장복
    • Proceedings of the IEEK Conference
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    • 2000.11a
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    • pp.181-184
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    • 2000
  • In this paper, the design of WDM network using the traffic estimation modeling is implemented. Because of the lack of data of real traffic volumes, the information of statistic data is used. using the modeling results, the WDM channels is assigned for each node, and the network is simulated using OPNET simulation tools. As a result, the realistic WDM network design for Korea topology is proposed.

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Component-Based Software Architecture for Biosystem Reverse Engineering

  • Lee, Do-Heon
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.10 no.5
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    • pp.400-407
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    • 2005
  • Reverse engineering is defined as the process where the internal structures and dynamics of a given system are inferred and analyzed from external observations and relevant knowledge. The first part of this paper surveys existing techniques for biosystem reverse engineering. Network structure inference techniques such as Correlation Matrix Construction (CMC), Boolean network and Bayesian network-based methods are explained. After the numeric and logical simulation techniques are briefly described, several representative working software tools were introduced. The second part presents our component-based software architecture for biosystem reverse engineering. After three design principles are established, a loosely coupled federation architecture consisting of 11 autonomous components is proposed along with their respective functions.

Toward the Efficient Integration of Travel Demand Analysis with Transportation Network Design Models (교통수요예칙과 가로망설계의 효율화)

  • 이인원
    • Journal of Korean Society of Transportation
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    • v.1 no.1
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    • pp.28-42
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    • 1983
  • In recent years, significant advances have been made enabling travel demand analysis and network design methods to be used as increasingly realistic evaluation tools. What has been lacking is the integration of travel demand analysis with network design models. This paper reviews some of advanced (integrated) modeling approaches and presents future research directions of integrated modeling system. To design urban transportation networks, it is argued that the travelers' free choice of mode, destination and route should be introduced into transportation network design procedure instead of assuming that trips from a zone to a workplace are fixed or deriving them in a normative procedure to achieve hypothetical system optima.

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Android Network Packet Monitoring & Analysis Using Wireshark and Debookee

  • Song, Mi-Hwa
    • International Journal of Internet, Broadcasting and Communication
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    • v.8 no.4
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    • pp.26-38
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    • 2016
  • Recently, mobile traffic has increased tremendously due to the deployment of smart devices such as smartphones and smart tablets. Android is the world's most powerful mobile platform in smartphone. The Android operating system provide seamless access to many applications and access to the Internet. It would involve network packet sharing communicated over the network. Network packet contains a lot of useful information about network activity that can be used as a description of the general network behaviours. To study what is the behaviours of the network packet, an effective tools such as network packet analyzers software used by network administrators to capture and analyze the network information. In this research, more understanding about network information in live network packet captured from Android smartphone is the target and identify the best network analyzer software.

Development of GIS-based Method for Estimating and Representing Stream Slopes Along the River Network (GIS 기반 하천경사 산정 및 하천망에 따른 표출 방식 개발)

  • You, Ho-Jun;Kim, Dong-Su;Yang, Sung-Kee
    • Journal of Environmental Science International
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    • v.21 no.6
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    • pp.725-738
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    • 2012
  • Recently, a variety of GIS-based tools enabling to generate topographic parameters for hydrologic and hydraulic researches have been developed. However, most of GIS-based tools are usually insufficient to estimate and visualize river channel slopes especially along the river network, which can be possibly utilized for many hydraulic equations such as Manning's formula. Many existing GIS-based tools have simply averaged cell-based slopes for the other advanced level of hydrologic units as likely as the mean watershed slope, thus that the river channel slope from the simple approach resulted in the inaccurate channel slope particularly for the mountain region where the slope varies significantly along the downstream direction. The paper aims to provide several more advanced GIS-based methodologies to assess the river channel slopes along the given river network. The developed algorithms were integrated with a newly developed tool named RiverSlope, which adapted theoretical formulas of river hydraulics to calculate channel slopes. For the study area, Han stream in the Jeju island was selected, where the channel slopes have a tendency to rapidly change the upstream near the Halla mountain and sustain the mild slope adjacent to watershed outlet heading for the ocean. The paper compared the simple slope method from the Arc Hydro, with other more complicated methods. The results are discussed to decide better approaches based on the given conditions.

Machine Tool State Monitoring Using Hierarchical Convolution Neural Network (계층적 컨볼루션 신경망을 이용한 공작기계의 공구 상태 진단)

  • Kyeong-Min Lee
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.2
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    • pp.84-90
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    • 2022
  • Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

A Content Analysis of Journal Articles Using the Language Network Analysis Methods (언어 네트워크 분석 방법을 활용한 학술논문의 내용분석)

  • Lee, Soo-Sang
    • Journal of the Korean Society for information Management
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    • v.31 no.4
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    • pp.49-68
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    • 2014
  • The purpose of this study is to perform content analysis of research articles using the language network analysis method in Korea and catch the basic point of the language network analysis method. Six analytical categories are used for content analysis: types of language text, methods of keyword selection, methods of forming co-occurrence relation, methods of constructing network, network analytic tools and indexes. From the results of content analysis, this study found out various features as follows. The major types of language text are research articles and interview texts. The keywords were selected from words which are extracted from text content. To form co-occurrence relation between keywords, there use the co-occurrence count. The constructed networks are multiple-type networks rather than single-type ones. The network analytic tools such as NetMiner, UCINET/NetDraw, NodeXL, Pajek are used. The major analytic indexes are including density, centralities, sub-networks, etc. These features can be used to form the basis of the language network analysis method.

Algorithms for Efficient Digital Media Transmission over IoT and Cloud Networking

  • Stergiou, Christos;Psannis, Kostas E.;Plageras, Andreas P.;Ishibashi, Yutaka;Kim, Byung-Gyu
    • Journal of Multimedia Information System
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    • v.5 no.1
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    • pp.27-34
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    • 2018
  • In recent years, with the blooming of Internet of Things (IoT) and Cloud Computing (CC), researchers have begun to discover new methods of technological support in all areas (e.g. health, transport, education, etc.). In this paper, in order to achieve a type of network that will provide more intelligent media-data transfer new technologies were studied. Additionally, we have been studied the use of various open source tools, such as CC analyzers and simulators. These tools are useful for studying the collection, the storage, the management, the processing, and the analysis of large volumes of data. The simulation platform which have been used for our research is CloudSim, which runs on Eclipse software. Thus, after measuring the network performance with CloudSim, we also use the Cooja emulator of the Contiki OS, with the aim to confirm and access more metrics and options. More specifically, we have implemented a network topology from a small section of the script of CloudSim with Cooja, so that we can test a single network segment. The results of our experimental procedure show that there are not duplicated packets received during the procedure. This research could be a start point for better and more efficient media data transmission.