• Title/Summary/Keyword: Research Network

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Development of AMI NMS (Network Management System) using SNMP for Network Monitoring of Meter Reading Devices (원격검침 설비의 네트워크 상태감시를 위한 SNMP 기반의 저압 AMI 망관리시스템 개발)

  • Kim, Young-Il;Park, So-Jeong;Kim, Young-Jun;Jung, Nam-Jun;Choi, Moon-Suk;Park, Byung-Seok
    • KEPCO Journal on Electric Power and Energy
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    • v.2 no.2
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    • pp.259-268
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    • 2016
  • KEPCO installed AMI (Advanced Metering Infrastructure) metering system for low-voltage customers from 2008. AMI metering system of KEPCO has operated 2.55 million customers and will plan to operate 22 million customers until 2020. KEPCO developed AMI NMS (Network Management System) to operate the meter reading network efficiently. NMS monitors the network status of DCUs (Data Concentration Unit) and modems. NMS provides functionalities of data collection and analysis. It collects property data of network device, network topology information, communication performance information, fault information, and etc. It analyzes collected data and controls network devices by remote access. AMI NMS collects about 370 MIBs (Mangement Information Bases) using SNMP (Simple Network Management Protocol). This paper introduces main functionalities, designed context, and implemented service screen.

Distributed memory access architecture and control for fully disaggregated datacenter network

  • Kyeong-Eun Han;Ji Wook Youn;Jongtae Song;Dae-Ub Kim;Joon Ki Lee
    • ETRI Journal
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    • v.44 no.6
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    • pp.1020-1033
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    • 2022
  • In this paper, we propose novel disaggregated memory module (dMM) architecture and memory access control schemes to solve the collision and contention problems of memory disaggregation, reducing the average memory access time to less than 1 ㎲. In the schemes, the distributed scheduler in each dMM determines the order of memory read/write access based on delay-sensitive priority requests in the disaggregated memory access frame (dMAF). We used the memory-intensive first (MIF) algorithm and priority-based MIF (p-MIF) algorithm that prioritize delay-sensitive and/or memory-intensive (MI) traffic over CPU-intensive (CI) traffic. We evaluated the performance of the proposed schemes through simulation using OPNET and hardware implementation. Our results showed that when the offered load was below 0.7 and the payload of dMAF was 256 bytes, the average round trip time (RTT) was the lowest, ~0.676 ㎲. The dMM scheduling algorithms, MIF and p-MIF, achieved delay less than 1 ㎲ for all MI traffic with less than 10% of transmission overhead.

Comparison of Recommendation Using Social Network Analysis with Collaborative Filtering in Social Network Sites (SNS에서 사회연결망 기반 추천과 협업필터링 기반 추천의 비교)

  • Park, Sangun
    • Journal of Information Technology Services
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    • v.13 no.2
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    • pp.173-184
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    • 2014
  • As social network services has become one of the most successful web-based business, recommendation in social network sites that assist people to choose various products and services is also widely adopted. Collaborative Filtering is one of the most widely adopted recommendation approaches, but recommendation technique that use explicit or implicit social network information from social networks has become proposed in recent research works. In this paper, we reviewed and compared research works about recommendation using social network analysis and collaborative filtering in social network sites. As the results of the analysis, we suggested the trends and implications for future research of recommendation in SNSs. It is expected that graph-based analysis on the semantic social network and systematic comparative analysis on the performances of social filtering and collaborative filtering are required.

An Efficient Network Attack Visualization Using Security Quad and Cube

  • Chang, Beom-Hwan;Jeong, Chi-Yoon
    • ETRI Journal
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    • v.33 no.5
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    • pp.770-779
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    • 2011
  • Security quad and cube (SQC) is a network attack analyzer that is capable of aggregating many different events into a single significant incident and visualizing these events in order to identify suspicious or illegitimate behavior. A network administrator recognizes network anomalies by analyzing the traffic data and alert messages generated in the security devices; however, it takes a lot of time to inspect and analyze them because the security devices generate an overwhelming amount of logs and security events. In this paper, we propose SQC, an efficient method for analyzing network security through visualization. The proposed method monitors anomalies occurring in an entire network and displays detailed information of the attacks. In addition, by providing a detailed analysis of network attacks, this method can more precisely detect and distinguish them from normal events.

Remote Monitoring with Hierarchical Network Architectures for Large-Scale Wind Power Farms

  • Ahmed, Mohamed A.;Song, Minho;Pan, Jae-Kyung;Kim, Young-Chon
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.1319-1327
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    • 2015
  • As wind power farm (WPF) installations continue to grow, monitoring and controlling large-scale WPFs presents new challenges. In this paper, a hierarchical network architecture is proposed in order to provide remote monitoring and control of large-scale WPFs. The network architecture consists of three levels, including the WPF comprised of wind turbines and meteorological towers, local control center (LCC) responsible for remote monitoring and control of wind turbines, and a central control center (CCC) that offers data collection and aggregation of many WPFs. Different scenarios are considered in order to evaluate the performance of the WPF communications network with its hierarchical architecture. The communications network within the WPF is regarded as the local area network (LAN) while the communication among the LCCs and the CCC happens through a wide area network (WAN). We develop a communications network model based on an OPNET modeler, and the network performance is evaluated with respect to the link bandwidth and the end-to-end delay measured for various applications. As a result, this work contributes to the design of communications networks for large-scale WPFs.

User Information Collection of Weibo Network Public Opinion under Python

  • Changhua Liu;Yanlin Han
    • Journal of Information Processing Systems
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    • v.19 no.3
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    • pp.310-322
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    • 2023
  • Although the network environment is gradually improving, the virtual nature of the network is still the same fact, which has brought a great influence on the supervision of Weibo network public opinion dissemination. In order to reduce this influence, the user information of Weibo network public opinion dissemination is studied by using Python technology. Specifically, the 2019 "Ethiopian air crash" event was taken as the research subject, the relevant data were collected by using Python technology, and the data from March 10, 2019 to June 20, 2019 were constructed by using the implicit Dirichlet distribution topic model and the naive Bayes classifier. The Weibo network public opinion user identity graph model under the "Ethiopian air crash" on June 20 found that the public opinion users of ordinary netizens accounted for the highest proportion and were easily influenced by media public opinion users. This influence is not limited to ordinary netizens. Public opinion users have an influence on other types of public opinion users. That is to say, in the network public opinion space of the "Ethiopian air crash," media public opinion users play an important role in the dissemination of network public opinion information. This research can lay a foundation for the classification and identification of user identity information types under different public opinion life cycles. Future research can start from the supervision of public opinion and the type of user identity to improve the scientific management and control of user information dissemination through Weibo network public opinion.

Design of Multiband Maritime Network for Ships and its Applications

  • Yun, Chang-Ho;Cho, A-Ra;Kim, Seung-Geun;Park, Jong-Won;Lim, Yong-Kon
    • Journal of information and communication convergence engineering
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    • v.7 no.3
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    • pp.314-322
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    • 2009
  • Nowadays, maritime communication systems need high data rate, reliability, and consistency in order to equivalently provide navigating ships with diverse multimedia services as in terrestrial communication systems. For this purpose, we conceptualize and design the maritime network for ships equipped with a multiband communication system which cost-effectively supports multimedia services according to several radiofrequency bands, such as HF, VHF, and satellite frequencies. We also introduce two service scenarios targeted for the maritime network; ship multimedia service (SMS) and real-time maritime logistics location tracking (RML2T). In addition, we specify related works according to three lower network layers (i.e., physical, data-link, and network layers) upon designing the network.

Architecture of Network Security Control Server for applying Security Policy Model (보안정책모델을 적용한 네트워크보안제어서버 구조)

  • Bang, Hyo-Chan;Kim, Ki-Young;Kim, Geon-Lyang;Jang, Jong-Soo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.10b
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    • pp.993-996
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    • 2001
  • 본 논문에서는 정책기반 네트워크보안 프레임워크의 전체적인 구조와 주요 아키텍쳐에 대해서 논하고 특히 보안정책 서버의 역할을 담당하는 네트워크보안제어서버의 구조와 메커니즘에 대해 구체적으로 기술한다.

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Multiple Reward Reinforcement learning control of a mobile robot in home network environment

  • Kang, Dong-Oh;Lee, Jeun-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1300-1304
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    • 2003
  • The following paper deals with a control problem of a mobile robot in home network environment. The home network causes the mobile robot to communicate with sensors to get the sensor measurements and to be adapted to the environment changes. To get the improved performance of control of a mobile robot in spite of the change in home network environment, we use the fuzzy inference system with multiple reward reinforcement learning. The multiple reward reinforcement learning enables the mobile robot to consider the multiple control objectives and adapt itself to the change in home network environment. Multiple reward fuzzy Q-learning method is proposed for the multiple reward reinforcement learning. Multiple Q-values are considered and max-min optimization is applied to get the improved fuzzy rule. To show the effectiveness of the proposed method, some simulation results are given, which are performed in home network environment, i.e., LAN, wireless LAN, etc.

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