• Title/Summary/Keyword: Network Partition

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A new model approach to predict the unloading rock slope displacement behavior based on monitoring data

  • Jiang, Ting;Shen, Zhenzhong;Yang, Meng;Xu, Liqun;Gan, Lei;Cui, Xinbo
    • Structural Engineering and Mechanics
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    • v.67 no.2
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    • pp.105-113
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    • 2018
  • To improve the prediction accuracy of the strong-unloading rock slope performance and obtain the range of variation in the slope displacement, a new displacement time-series prediction model is proposed, called the fuzzy information granulation (FIG)-genetic algorithm (GA)-back propagation neural network (BPNN) model. Initially, a displacement time series is selected as the training samples of the prediction model on the basis of an analysis of the causes of the change in the slope behavior. Then, FIG is executed to partition the series and obtain the characteristic parameters of every partition. Furthermore, the later characteristic parameters are predicted by inputting the earlier characteristic parameters into the GA-BPNN model, where a GA is used to optimize the initial weights and thresholds of the BPNN; in the process, the numbers of input layer nodes, hidden layer nodes, and output layer nodes are determined by a trial method. Finally, the prediction model is evaluated by comparing the measured and predicted values. The model is applied to predict the displacement time series of a strong-unloading rock slope in a hydropower station. The engineering case shows that the FIG-GA-BPNN model can obtain more accurate predicted results and has high engineering application value.

Prolong life-span of WSN using clustering method via swarm intelligence and dynamical threshold control scheme

  • Bao, Kaiyang;Ma, Xiaoyuan;Wei, Jianming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.6
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    • pp.2504-2526
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    • 2016
  • Wireless sensors are always deployed in brutal environments, but as we know, the nodes are powered only by non-replaceable batteries with limited energy. Sending, receiving and transporting information require the supply of energy. The essential problem of wireless sensor network (WSN) is to save energy consumption and prolong network lifetime. This paper presents a new communication protocol for WSN called Dynamical Threshold Control Algorithm with three-parameter Particle Swarm Optimization and Ant Colony Optimization based on residual energy (DPA). We first use the state of WSN to partition the region adaptively. Moreover, a three-parameter of particle swarm optimization (PSO) algorithm is proposed and a new fitness function is obtained. The optimal path among the CHs and Base Station (BS) is obtained by the ant colony optimization (ACO) algorithm based on residual energy. Dynamical threshold control algorithm (DTCA) is introduced when we re-select the CHs. Compared to the results obtained by using APSO, ANT and I-LEACH protocols, our DPA protocol tremendously prolongs the lifecycle of network. We observe 48.3%, 43.0%, and 24.9% more percentages of rounds respectively performed by DPA over APSO, ANT and I-LEACH.

Optimal Design of Location Management Using Particle Swarm Optimization (파티클군집최적화 방법을 적용한 위치관리시스템 최적 설계)

  • Byeon, Ji-Hwan;Kim, Sung-Soo;Jang, Si-Hwan;Kim, Yeon-Soo
    • Korean Management Science Review
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    • v.29 no.1
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    • pp.143-152
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    • 2012
  • Location area planning (LAP) problem is to partition the cellular/mobile network into location areas with the objective of minimizing the total cost in location management. The minimum cost has two components namely location update cost and searching cost. Location update cost is incurred when the user changes itself from one location area to another in the network. The searching cost incurred when a call arrives, the search is done only in the location area to find the user. Hence, it is important to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking cost is a minimum. The complete mobile network is divided into location areas. Each location area consists of a group of cells. This partitioning problem is a difficult combinatorial optimization problem. In this paper, we use particle swarm optimization (PSO) to obtain the best/optimal group of cells for 16, 36, 49, and 64 cells network. Experimental studies illustrate that PSO is more efficient and surpasses those of precious studies for these benchmarking problems.

Optimal ELAN Configuration for Scaling Broadcast Traffic in a LAN Emulation Network (LANE망에서의 scalable한 broadcast traffic 관리를 위한 최적 ELAN 구성방법)

  • 손종희;김도훈;차동완
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2000.04a
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    • pp.691-694
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    • 2000
  • 기존 LAN 환경에서 인터넷을 이용한 멀티미디어 실시간 전송과 같은 QoS 보장형 서비스에 대한 요구가 증대되면서, 고속의 ATM 기술을 LAN에 적용하는 기술들이 등장하였다. LANE(LAN Emulation)은 그러한 기술 대안들 중에서 campus network와 enterprise network에 많이 보급되고 있는 기술이다. 그러나 이러한 급격한 LANE 도입에 비하여 이의 효과적인 운용에 대한 연구는 많지 않은 실정이다. 본 논문에서는 LANE을 도입한 campus network의 최적 운영방안에 대하여 논한다. Broadcast 데이터 트래픽 관리에서 발생하는 규모성(Scalability) 문제로 인하여 전체 LANE망은 여러 개의 ELAN으로 나뉘어 관리된다. 이 때 하나의 ELAN은 마치 단위 LAN로써, Broadcast 데이터의 전송범위를 제한한다. 즉, 서로 다른 ELAN에 속하는 노드간에는 Broadcast 방식으로 데이터를 전송할 수 없게 된다. 그런데, IPX 등을 사용하는 대화형 시뮬레이션 게임 등과 같은 응용프로그램에서는 Broadcast 방식이 이용되므로, 서로 다른 ELAN에 속하는 노드간의 데이터 전송은 불가능하게 되거나 별도의 복잡한 과정을 개입시켜야 하는 비용이 발생한다. 따라서 규모성 문제해결을 위한 ELAN 구성(configuration)에는 위와 같은 비용이 수반된다. 본 연구에서는 LANE망을 여러 개의 ELAN으로 분할하는 경우에 블로킹(blocking) 되는 Broadcast 트래픽 규모를 해당 ELAN 구성의 비용으로 간주한다. 이 경우에 규모성을 고려한 ELAN의 최적 구현방안(optimal configuration)은 ELAN 구성을 위한 기술적 제약하에서 블로킹되는 Broadcast 트래픽을 최소화시키는 문제로 요약된다. 이는 다시 그래프 분할문제(graph partition problem)의 변형된 형태로 모형화 될 수 있다. 본 논문에서는 이러한 사항들을 고려하여 제시된 수리적 모형을 대상으로, genetic algorithm을 이용하여 최적 ELAN 구성을 위한 여러 파라미터들의 효과를 살펴보고, 이러한 결과들이 LANE 운영과 관련하여 가지는 함축적인 의미를 고찰한다.

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An Efficient Overlay Multi-cast Scheduling for Next Generation Internet VOD Service (차세대 인터넷 VOD 서비스를 위한 효율적인 오버레이 멀티캐스트 스케줄링)

  • Choi, Sung-Wook
    • Journal of the Korea Computer Industry Society
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    • v.9 no.2
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    • pp.53-62
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    • 2008
  • Intensive studies have been made in the area of IPTV VOD server. The basic goal of the study is to find an efficient mechanism to allow maximum number of users under the limited resources such as Buffer utilization, disk performance and network bandwidth. The overlay multicast that has been recently presented as an alternative for the IP multicast has been getting much persuasion by the system resource and the network bandwidth and the advancement of the network cost. we propose a efficient overlay multi_casting network policy for multimedia services with multi media partition storage. Simulation results show that the rate of service number and service time of proposed scheme are about 23% performance improved than that of traditional methods. This implies that our method can allow much more users for given resources.

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Improving the Performances of the Neural Network for Optimization by Optimal Estimation of Initial States (초기값의 최적 설정에 의한 최적화용 신경회로망의 성능개선)

  • 조동현;최흥문
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.8
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    • pp.54-63
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    • 1993
  • This paper proposes a method for improving the performances of the neural network for optimization by an optimal estimation of initial states. The optimal initial state that leads to the global minimum is estimated by using the stochastic approximation. And then the update rule of Hopfield model, which is the high speed deterministic algorithm using the steepest descent rule, is applied to speed up the optimization. The proposed method has been applied to the tavelling salesman problems and an optimal task partition problems to evaluate the performances. The simulation results show that the convergence speed of the proposed method is higher than conventinal Hopfield model. Abe's method and Boltzmann machine with random initial neuron output setting, and the convergence rate to the global minimum is guaranteed with probability of 1. The proposed method gives better result as the problem size increases where it is more difficult for the randomized initial setting to give a good convergence.

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Femtocell Subband Selection Method for Managing Cross- and Co-tier Interference in a Femtocell Overlaid Cellular Network

  • Kwon, Young Min;Choo, Hyunseung;Lee, Tae-Jin;Chung, Min Young;Kim, Mihui
    • Journal of Information Processing Systems
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    • v.10 no.3
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    • pp.384-394
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    • 2014
  • The femtocell overlaid cellular network (FOCN) has been used to enhance the capacity of existing cellular systems. To obtain the desired system performance, both cross-tier interference and co-tier interference in an FOCN need to be managed. This paper proposes an interference management scheme that adaptively constructs a femtocell cluster, which is a group of femtocell base stations that share the same frequency band. The performance evaluation shows that the proposed scheme can enhance the performance of the macrocell-tier and maintain a greater signal to interference-plus-noise ratio than the outage level can for about 99% of femtocell users.

A Procedure for Determining The Locating Chromatic Number of An Origami Graphs

  • Irawan, Agus;Asmiati, Asmiati;Utami, Bernadhita Herindri Samodra;Nuryaman, Aang;Muludi, Kurnia
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.31-34
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    • 2022
  • The concept of locating chromatic number of graph is a development of the concept of vertex coloring and partition dimension of graph. The locating-chromatic number of G, denoted by χL(G) is the smallest number such that G has a locating k-coloring. In this paper we will discussed about the procedure for determine the locating chromatic number of Origami graph using Python Programming.

COMPUTATION OF SOMBOR INDICES OF OTIS(BISWAPPED) NETWORKS

  • Basavanagoud, B.;Veerapur, Goutam
    • Journal of the Chungcheong Mathematical Society
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    • v.35 no.3
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    • pp.205-225
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    • 2022
  • In this paper, we derive analytical closed results for the first (a, b)-KA index, the Sombor index, the modified Sombor index, the first reduced (a, b)-KA index, the reduced Sombor index, the reduced modified Sombor index, the second reduced (a, b)-KA index and the mean Sombor index mSOα for the OTIS biswapped networks by considering basis graphs as path, wheel graph, complete bipartite graph and r-regular graphs. Network theory plays a significant role in electronic and electrical engineering, such as signal processing, networking, communication theory, and so on. A topological index (TI) is a real number associated with graph networks that correlates chemical networks with a variety of physical and chemical properties as well as chemical reactivity. The Optical Transpose Interconnection System (OTIS) network has recently received increased interest due to its potential uses in parallel and distributed systems.

Design of a Partitionable Single-Stage Shuffle-Exchange Network (분할 가능한 단단계(Single-Stage) Shuffle-Exchange 네트워크의 설계)

  • Lee, Jae-Dong
    • Journal of KIISE:Computer Systems and Theory
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    • v.30 no.3_4
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    • pp.130-137
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    • 2003
  • This paper presents the problem of partitioning the Single-Stage Shuffle-Exchange Network(SSEN). An algorithm, named SSEN_to_PSEN, is devised to transform an SSEN into a Partitionable Shuffle-Exchange Network (PSEN). The proposed algorithm presents that the SSEN can be partitioned into independent sub-networks without additional links for N $\leq$ 8. Additional links are needed in order to partition an SSEN, but only when N $\geq$ 16. The running time of the algorithm SSEN_to_PSEN is $\theta$(NlogN). By comparing with a hypercube network, the PSEN is less expensive than a hypercube network even when some additional links are added. By partitioning, a large PSEN in a massively parallel machine can compute various problems for multiple users simultaneously, thereby the processing efficiency of the machine is improved.