• Title/Summary/Keyword: Weighted Network

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State-Dependent Call Admission Control in Hierarchical Wireless Multiservice Networks

  • Chung Shun-Ping;Lee Jin-Chang
    • Journal of Communications and Networks
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    • v.8 no.1
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    • pp.28-37
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    • 2006
  • State-dependent call admission control (SDCAC) is proposed to make efficient use of scarce wireless resource in a hierarchical wireless network with heterogeneous traffic. With SDCAC, new calls are accepted according to an acceptance probability taking account of not only cell dwell time but also call holding time and system state (i.e., occupied bandwidth). An analytical method is developed to calculate performance measures of interest, e.g., new call blocking probability, forced termination probability, over. all weighted blocking probability. Numerical results with not only stationary but nonstationary traffic loads are presented to show the robustness of SDCAC. It is shown that SDCAC performs much better than the other considered schemes under nonstationary traffic load.

A Network Partitioning Using the Concept of Conection Index-Algorithm and Implementation (연결지수의 개념을 사용한 회로망분실-알고리즘 및 실시)

  • 박진섭;박송배
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.21 no.6
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    • pp.94-104
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    • 1984
  • Based on a new concept of connection index of a weighted graph, a new efficient houris tic algorithm of 0(v.e) for network partitioning is presented, where v and e are the number of nodes and edges, respectively. Experimental results show that our algorithm is very efficient and yields an optimal or near optimal solution for a number of partitioning problems tested. Some applications of the proposed algorithm are suggested and its computer implementation is described in detail.

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Design of high speed weighted FDNN applied DWW algorithm (DWW 알고리즘을 적용한 고속 가중 FDNN의 설계)

  • 이철희;변오성;문성룡
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.7
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    • pp.101-108
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    • 1998
  • In this paper, after we got to realized FDNN (fuzzy decision neural network) applied the quantization triangularity fuzzy function to DBNN(decision based neural network) of a hierarchical structure for image process, we could esign hardware of the realized FDNN. Also it is normalized the standard image and the input image as the same size. We are applied DWW algorithm which selected the closest value with finding similarity of an interval image by this distance to FDNN. So we could calulated in terms of distance to weight of pixel which composed two image and eliminated the nise of image, minimized the lost of information, obtained the optimal information. It is designed hardware of high speed weighted FDNN using COMPASS tool. Aslo, the total circuit is realized as gates of 61,000 and could show to superiority of FDNN using the simulation.

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Bandwidth Allocation and Scheduling Algorithms for Ethernet Passive Optical Networks

  • Joo, Un-Gi
    • Management Science and Financial Engineering
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    • v.16 no.1
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    • pp.59-79
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    • 2010
  • This paper considers bandwidth allocation and scheduling problems on Ethernet Passive Optical Networks (EPON). EPON is one of the good candidates for the optical access network. This paper formulates the bandwidth allocation problem as a nonlinear mathematical one and characterizes the optimal bandwidth allocation which maximizes weighted sum of throughput and fairness. Based upon the characterization, two heuristic algorithms are suggested with various numerical tests. The test results show that our algorithms can be used for efficient bandwidth allocation on the EPON. This paper also shows that the WSPT (Weighted Shortest Processing Time) rule is optimal for minimization the total delay time in transmitting the traffic of the given allocated bandwidth.

Distributed and Weighted Clustering based on d-Hop Dominating Set for Vehicular Networks

  • Shi, Yan;Xu, Xiang;Lu, Changkai;Chen, Shanzhi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.4
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    • pp.1661-1678
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    • 2016
  • Clustering is one of the key technologies in vehicular networks. Constructing and maintaining stable clusters is a challenging task in high mobility environments. DWCM (Distributed and Weighted Clustering based on Mobility Metrics) is proposed in this paper based on the d-hop dominating set of the network. Each vehicle is assigned a priority that describes the cluster relationship. The cluster structure is determined according to the d-hop dominating set, where the vehicles in the d-hop dominating set act as the cluster head nodes. In addition, cluster maintenance handles the cluster structure changes caused by node mobility. The rationality of the proposed algorithm is proven. Simulation results in the NS-2 and VanetMobiSim integrated environment demonstrate the performance advantages.

Rumbling Index Development for a Passenger Car (승용차의 럼블링 음질 인덱스 개발)

  • 채희창;박동철;정승균;이상권
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.628-634
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    • 2003
  • Rumbling sound is one of the most important interior sound of a passenger cu. The conventional rumbling noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the rumbling sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psycoacoustics. According to recent research results, the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network th[ ory has been applied to derivation of sound quality index fur rumbling sound of a passenger car.

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Pole-Zero Assignment Self-Tuning Controller Using Neural Network (신경회로망 기법을 이용한 극-영점 배치 자기 동조 제어기)

  • 구영모;이윤섭;장석호;우광방
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.40 no.2
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    • pp.183-191
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    • 1991
  • This paper develops a pole-zero assignment self-tuning regulator utilizing the method of a neural network in the plant parameter estimation. An approach to parameter estimation of the plant with a Hopfield neural network model is proposed, and the control characteristics of the plant are evaluated by means of a simulation for a second-order linear time invariant plant. The results obtained with those of Exponentially Weighted Recursive Least Squares(EWRLS) method are also shown.

Weighted Association Rule Discovery for Item Groups with Different Properties (상이한 특성을 갖는 아이템 그룹에 대한 가중 연관 규칙 탐사)

  • 김정자;정희택
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.6
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    • pp.1284-1290
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    • 2004
  • In market-basket analysis, weighted association rule(WAR) discovery can mine the rules which include more beneficial information by reflecting item importance for special products. However, when items are divided into more than one group and item importance for each group must be measured by different measurement or separately, we cannot directly apply traditional weighted association rule discovery. To solve this problem, we propose a novel methodology to discovery the weighted association rule in this paper In this methodology, the items should be first divided into sub-groups according to the properties of the items, and the item importance is defined or calculated only with the items enclosed to the sub-group. Our algorithm makes qualitative evaluation for network risk assessment possible by generating risk rule set for risk factor using network sorority data, and quantitative evaluation possible by calculating risk value using statistical factors such as weight applied in rule generation. And, It can be widely used for new model of more delicate analysis in market-basket database in which the data items are distinctly separated.

Generation of Collaboration Network and Analysis of Researcher's Role in National Cancer Center (협업네트워크 구축과 연구자 역할 분석 -국립암센터 사례 중심으로-)

  • Jang, Hae-Lan
    • The Journal of the Korea Contents Association
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    • v.15 no.10
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    • pp.387-399
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    • 2015
  • Recently collaboration network is generated to find out experts in their field as potential collaborators in health care sector. In this paper, the co-author network of a National Cancer Center researcher was generated for identifying each researcher's role and collaborative research pattern. The co-author network of 2,437 authors was extracted from 1,194 SCI(E) publications from 2000 to 2010 and author's role was analyzed by author's centrality value. Centrality reflecting only the number of papers and centrality weighted by the paper number, impact factor, and authorship contribution was evaluated. On the comparison with simple degree centrality value and the weighted degree centrality, difference of value was statistically significant(t=11.66, p=0.00). Co-author network considering various variables of the paper provides more objective figure of researcher's role. This suggests that co-author network could be more effective in identifying potential collaborators.