• Title/Summary/Keyword: computer network

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A supervised-learning-based spatial performance prediction framework for heterogeneous communication networks

  • Mukherjee, Shubhabrata;Choi, Taesang;Islam, Md Tajul;Choi, Baek-Young;Beard, Cory;Won, Seuck Ho;Song, Sejun
    • ETRI Journal
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    • v.42 no.5
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    • pp.686-699
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    • 2020
  • In this paper, we propose a supervised-learning-based spatial performance prediction (SLPP) framework for next-generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data to react to network performance changes, it is highly beneficial to perform accurate performance prediction for different systems to support various network functions. Recent advancements in complex statistical algorithms and computational efficiency have made machine-learning ubiquitous for accurate data-based prediction. A robust network performance prediction framework for optimizing performance and resource utilization through a linear discriminant analysis-based prediction approach has been proposed in this paper. Comparison results with different machine-learning techniques on real-world data demonstrate that SLPP provides superior accuracy and computational efficiency for both stationary and mobile user conditions.

Handwritten Indic Digit Recognition using Deep Hybrid Capsule Network

  • Mohammad Reduanul Haque;Rubaiya Hafiz;Mohammad Zahidul Islam;Mohammad Shorif Uddin
    • International Journal of Computer Science & Network Security
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    • v.24 no.2
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    • pp.89-94
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    • 2024
  • Indian subcontinent is a birthplace of multilingual people where documents such as job application form, passport, number plate identification, and so forth is composed of text contents written in different languages/scripts. These scripts may be in the form of different indic numerals in a single document page. Due to this reason, building a generic recognizer that is capable of recognizing handwritten indic digits written by diverse writers is needed. Also, a lot of work has been done for various non-Indic numerals particularly, in case of Roman, but, in case of Indic digits, the research is limited. Moreover, most of the research focuses with only on MNIST datasets or with only single datasets, either because of time restraints or because the model is tailored to a specific task. In this work, a hybrid model is proposed to recognize all available indic handwritten digit images using the existing benchmark datasets. The proposed method bridges the automatically learnt features of Capsule Network with hand crafted Bag of Feature (BoF) extraction method. Along the way, we analyze (1) the successes (2) explore whether this method will perform well on more difficult conditions i.e. noise, color, affine transformations, intra-class variation, natural scenes. Experimental results show that the hybrid method gives better accuracy in comparison with Capsule Network.

Korean Restaurant Reservation System Model Using Hybrid Code Network (Hybrid Code Network를 이용한 한국어 식당 예약 시스템 모델)

  • Lee, Dong-Yub;Hur, Yun-A;Lim, Heui-Seok
    • Proceedings of The KACE
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    • 2017.08a
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    • pp.57-59
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    • 2017
  • 대화 시스템(dialogue system)은 텍스트나 음성을 통해 다양한 분야에서 특정한 목적을 수행할 수 있는 시스템이다. 대화 시스템을 구현하기 위한 방법으로 인공 신경망(neural network)을 기반으로한 end-to-end learning 방식이 제안되었다. End-to-end learning 방식을 이용한 식당 예약 시스템 모델의 학습을 위해 페이스북은 영어로 이루어진 식당 예약에 관련된 학습 대화 데이터셋(The 6 dialog bAbI tasks)을 구축하였다. 하지만 end-to-end learning 방식의 학습은 많은 학습 데이터가 필요하다는 단점이 존재하는데, 액션 템플릿(action template)의 정의를 통해 도메인 지식을 표현함으로써 일반적인 end-to-end learning 방식보다 적은 학습량으로 좋은 성능의 모델을 학습할 수 있는 Hybrid Code Network 구조를 제안한 연구가 있다. 본 논문에서는 Hybrid Code Network 구조를 이용하여 한국어 식당 예약 시스템을 구축할 수 있는 방법을 제안하고, 한국어로 이루어진 식당 예약에 관련한 학습 대화 데이터를 구축하는 방법을 제안한다.

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Packet Payload-based Network Traffic Classification using Convolutional Neural Network (Convolutional Neural Network을 활용한 패킷 페이로드 기반 네트워크 트래픽 분류)

  • Kim, Ju-Bong;Lim, Hyun-Kyo;Heo, Joo-Seong;Han, Youn-Hee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.04a
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    • pp.928-931
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    • 2017
  • 네트워크 트래픽 데이터를 정제하여, Convolutional Neural Network Model 훈련에 적합한 데이터 세트로 변환하는데, 그 방법은 패킷 단위의 트래픽 데이터를 이미지 형태로 만드는 것이다. 완성된 데이터 세트를 훈련데이터로 하여 Convolutional Neural Network Model에 훈련하고, 훈련데이터의 이미지 크기를 변환해가며 훈련시킨 결과에 대해 비교 분석 및 평가를 진행한다.

An on-line non-invasive network monitor for the SPAX parallel computer (SPAX 병렬 컴퓨터에서의 온라인 무간섭 네트워크 성능 감시기)

  • 이승구
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.6
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    • pp.44-50
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    • 1997
  • This paper describes the design and test of an on-line non-invasive network performance monitor (hardware portion) for the SPAX parallel computer. The SPAX parallel computer supports up to 256 intel P6 processors with 4 P6 processors constituting a processign node. The nodes are interconnected with a dual two-level crossbar network calle dXcent-net. Since the performance of the SPAX parallel computer is highly dependent on the proper and efficient operation of the network, an on-line non-invasive network performance monitor (with hardware components) has been developed to aid in the monitoring and tunign of the Xcent-net. Successful testing of a prototype node monitor board and PC interface system shows that our monitor design provides a low-cost practical solution to this problem.

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A Fault-Tolerant Multistage Interconnection Network with Self-Loop Switch (자기 루프 스위치를 가진 결함-허용 다단계 상호연결망)

  • Kim, Gum-Ho;Kim, Hyung-Wook;Nam, Soon-Hyun;Youn, Sung-Dae
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.04a
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    • pp.231-234
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    • 2001
  • 본 논문은 다단계 상호연결망에서 높은 처리율과 결함 허용을 위해 중복 경로를 제공하는 E-Cube-network 구조를 제안한다. Cube network의 확장된 형태인 E(Extended)-Cube network 구조를 통해 패킷 전송중 충돌이 발생한 경우 스위치 자신을 순환하고, 재차 충돌이 발생하면 멀티플렉서를 통해 또 다른 새로운 경로로 패킷을 전송하는 새로운 알고리즘을 제시한다. 그리고 모의실험을 통해 기존의 Cube network 구조보다 높은 종단간 처리율을 보인다.

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Bottleneck-based Siam-CNN Algorithm for Object Tracking (객체 추적을 위한 보틀넥 기반 Siam-CNN 알고리즘)

  • Lim, Su-Chang;Kim, Jong-Chan
    • Journal of Korea Multimedia Society
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    • v.25 no.1
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    • pp.72-81
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    • 2022
  • Visual Object Tracking is known as the most fundamental problem in the field of computer vision. Object tracking localize the region of target object with bounding box in the video. In this paper, a custom CNN is created to extract object feature that has strong and various information. This network was constructed as a Siamese network for use as a feature extractor. The input images are passed convolution block composed of a bottleneck layers, and features are emphasized. The feature map of the target object and the search area, extracted from the Siamese network, was input as a local proposal network. Estimate the object area using the feature map. The performance of the tracking algorithm was evaluated using the OTB2013 dataset. Success Plot and Precision Plot were used as evaluation matrix. As a result of the experiment, 0.611 in Success Plot and 0.831 in Precision Plot were achieved.

Novel Two-Level Randomized Sector-based Routing to Maintain Source Location Privacy in WSN for IoT

  • Jainulabudeen, A.;Surputheen, M. Mohamed
    • International Journal of Computer Science & Network Security
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    • v.22 no.3
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    • pp.285-291
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    • 2022
  • WSN is the major component for information transfer in IoT environments. Source Location Privacy (SLP) has attracted attention in WSN environments. Effective SLP can avoid adversaries to backtrack and capture source nodes. This work presents a Two-Level Randomized Sector-based Routing (TLRSR) model to ensure SLP in wireless environments. Sector creation is the initial process, where the nodes in the network are grouped into defined sectors. The first level routing process identifies sector-based route to the destination node, which is performed by Ant Colony Optimization (ACO). The second level performs route extraction, which identifies the actual nodes for transmission. The route extraction is randomized and is performed using Simulated Annealing. This process is distributed between the nodes, hence ensures even charge depletion across the network. Randomized node selection process ensures SLP and also avoids depletion of certain specific nodes, resulting in increased network lifetime. Experiments and comparisons indicate faster route detection and optimal paths by the TLRSR model.

Parallel Paths in Honeycomb Network (Honeycomb 연결망에서의 병렬 경로)

  • Kim, Cheol;Lee, Hyeong-Ok;Lim, Hyeong-Seok
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.297-300
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    • 1998
  • A honeycomb network is considered as a multiprocessor interconnection network. The network cost defined as the product of degree and diameter is better for honeycomb networks than for other types of meshes. Parallel paths offer us bypasses when the networks have faulty nodes or edges. In this paper, we present a method to construct a parallel path in honeycomb network, and show that the fault diameter for the honeycomb network is d+8, where d is diameter of the honeycomb network.

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An Integrated QoS Support Architecture for Wireless Home Network Based on IEEE 802.11 Wireless LAN

  • Hong, Sung-Hwa;Kim, Byoung-Kug;Eom, Doo-Seop
    • Journal of IKEEE
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    • v.11 no.4
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    • pp.227-234
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    • 2007
  • In this paper, to support a QoS level appropriate to the user in Wireless Home Network based Wireless LAN, we propose a QoS support architecture which includes Wired Network and Wireless Network. Actually, an important problem to support QoS in Wireless Home Network is approached not only on a MAC level in Wireless LAN but also on a integrated method to combine Network layer with Datalink layer. By applying the integrated QoS support method, it is possible to provide QoS support architecture using a Wireless LAN terminal with a minimum changing, and the proposed scheme has advantage of QoS support method, which is more superior than a existing scheme to support QoS in MAC level of Wireless LAN. Simulations results show that overall performance of the proposed scheme can be improved.

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