• Title/Summary/Keyword: tree network

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Energy Efficient IDS Node Distribution Algorithm using Minimum Spanning Tree in MANETs

  • Ha, Sung Chul;Kim, Hyun Woo
    • Smart Media Journal
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    • v.5 no.4
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    • pp.41-48
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    • 2016
  • In mobile ad hoc networks(MANETs), all the nodes in a network have limited resources. Therefore, communication topology which has long lifetime is suitable for nodes in MANETs. And MANETs are exposed to various threats because of a new node which can join the network at any time. There are various researches on security problems in MANETs and many researches have tried to make efficient schemes for reducing network power consumption. Power consumption is necessary to secure networks, however too much power consumption can be critical to network lifetime. This paper focuses on energy efficient monitoring node distribution for enhancing network lifetime in MANETs. Since MANETs cannot use centralized infrastructure such as security systems of wired networks, we propose an efficient IDS node distribution scheme using minimum spanning tree (MST) method to cover all the nodes in a network and enhance the network lifetime. Simulation results show that the proposed algorithm has better performance in comparison with the existing algorithms.

A Genetic Algorithm for Real-Time Multicast Routing (실시간 멀티캐스트 라우팅을 위한 유전자 알고리즘)

  • 서용만;한치근
    • Journal of the Korean Operations Research and Management Science Society
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    • v.25 no.3
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    • pp.81-89
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    • 2000
  • The real-time multicast problem is to construct a multicast tree starting from a source node and including multiple destination nodes and that has minimum network cost with delay constraints. It is known that to find a tree of the minimum network cost is the Steiner Tree problem which is NP-complete. In this paper, we propose a genetic algorithm to solve the multicast tree with minimum network cost and the delay constraints. The computational results obtained by comparing an existing algorithm. Kompella algorithm, and the proposed algorithm show that our algorithm tends to find lower network cost on the average than Kompella algorithm does.

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A dynamic multicast routing algorithm in ATM networks (ATM 망에서 동적 멀티캐스트 루팅 알고리즘)

  • 류병한;김경수;임순용
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.11
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    • pp.2477-2487
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    • 1997
  • In this paepr, we propose a dynamic multicast routin algorithm for constructing the delay-constrained minimal spanning tree in the VP-based ATM networks, in which we consider the effiiciency enen in the case wheree the destination dynamically joins/departs the multicast connection. For constructing the delay-constrained spanning tree, we frist generate a reduced network consisting of only VCX nodes from a given ATM network, originally consisting of VPX/VCX nodes. Then, we obtain the delay-constrained spanning tree with a minimal tree cost on the reduced network by using our proposed heuristic algorithm. Through numerical examples, we show that our dynamic multicast routing algorithm can provide an efficient usage of network resources when the membership nodes frequently changes during the lifetime of a multicast connection. We also demonstrate the more cost-saving can be expected in dense networks when applyingour proposed algorithm.

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Analytical modeling of a Fat-tree Network with buffered a$\times$b switches (버퍼를 장착한 a$\times$b 스위치로 구성된 Fat-tree 망의 성능분석)

  • 신태지;양명국
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.374-377
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    • 2003
  • In this paper, a performance evaluation model of the Fat-Tree network with the multiple-buffered crossbar switches is proposed and examined. Buffered switch technique is well known to solve the data collision problem in the switch network The proposed evaluation model is developed by investigating the transfer patterns of data packets in a switch with output-buffers. Steady state probability concept is used to simplify the analyzing processes. Two important parameters of the network performance, throughput and delay, are then evaluated. To validate the proposed analysis model, the simulation is carried out on the various sizes of Fat-tree networks that use the multiple a$\times$b buffered crossbar switches. It is observed that both analysis and simulation results are match closely.

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Optimal Terminal Interconnection Reconstruction along with Terminal Transition in Randomly Divided Planes

  • Youn, Jiwon;Hwang, Byungyeon
    • Journal of information and communication convergence engineering
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    • v.20 no.3
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    • pp.160-165
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    • 2022
  • This paper proposes an efficient method of reconstructing interconnections when the terminals of each plane change in real-time situations where randomly divided planes are interconnected. To connect all terminals when the terminals of each plane are changed, we usually reconstruct the interconnections between all terminals. This ensures a minimum connection length, but it takes considerable time to reconstruct the interconnection for the entire terminal. This paper proposes a solution to obtain an optimal tree close to the minimum spanning tree (MST) in a short time. The construction of interconnections has been used in various design-related areas, from networks to architecture. One of these areas is an ad hoc network that only consists of mobile hosts and communicates with each other without a fixed wired network. Each host of an ad hoc network may appear or disappear frequently. Therefore, the heuristic proposed in this paper may expect various cost savings through faster interconnection reconstruction using the given information in situations where the connection target is changing.

Improved Decision Tree Classification (IDT) Algorithm For Social Media Data

  • Anu Sharma;M.K Sharma;R.K Dwivedi
    • International Journal of Computer Science & Network Security
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    • v.24 no.6
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    • pp.83-88
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    • 2024
  • In this paper we used classification algorithms on social networking. We are proposing, a new classification algorithm called the improved Decision Tree (IDT). Our model provides better classification accuracy than the existing systems for classifying the social network data. Here we examined the performance of some familiar classification algorithms regarding their accuracy with our proposed algorithm. We used Support Vector Machines, Naïve Bayes, k-Nearest Neighbors, decision tree in our research and performed analyses on social media dataset. Matlab is used for performing experiments. The result shows that the proposed algorithm achieves the best results with an accuracy of 84.66%.

Design and Implementation of a Genetic Algorithm for Global Routing (글로벌 라우팅 유전자 알고리즘의 설계와 구현)

  • 송호정;송기용
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.2
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    • pp.89-95
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    • 2002
  • Global routing is to assign each net to routing regions to accomplish the required interconnections. The most popular algorithms for global routing inlcude maze routing algorithm, line-probe algorithm, shortest path based algorithm, and Steiner tree based algorithm. In this paper we propose weighted network heuristic(WNH) as a minimal Steiner tree search method in a routing graph and a genetic algorithm based on WNH for the global routing. We compare the genetic algorithm(GA) with simulated annealing(SA) by analyzing the results of each implementation.

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New Tree Routing Protocol with Adaptive Metrics Based on Hop Count

  • BeomKyu Suh;Ismatov Akobir;Ki-Il Kim
    • Journal of information and communication convergence engineering
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    • v.22 no.3
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    • pp.207-214
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    • 2024
  • In wireless sensor networks, the implementation of routing protocols is crucial owing to their limited computational capacities. Tree routing is a suitable method in wireless sensors owing to its minimal routing overhead. However, single-hop metric schemes, such as hop count, cause congestion at specific nodes, whereas multiple metric schemes cannot control dynamically changing network environments. To address these issues, we propose a scheme to implement enhanced tree routing with adaptive metrics based on hop count. This approach assigns different weights to metrics to select suitable parent nodes based on hop count. The parent-selection algorithm utilizes hop count, buffer occupancy, and received signal strength indicator (RSSI) as metrics. This study evaluates the performance through simulation scenarios to analyze whether improvements can be made to address problems encountered in traditional tree routing. The performance metrics include packet delivery speed, throughput, and end-to-end delay, which vary depending on the volume of network traffic.

Multicast Copy Network with Internet Buffered B-Tree(IBBT) Network (내부버퍼 B-Tree 네트워크를 사용한 멀티캐스트 복사망)

  • 신재구;손유익
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04a
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    • pp.490-492
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    • 2001
  • 본 논문은 ATM 멀티캐스트 스위치를 위한 새로운 복사망을 제안하였다. Lee의 복사망과 그 이후 제안된 복사망에서 문제가 된 오버플로우와 충돌 문제를 해결하기 위해 다중경로와 다중출력을 갖는 B-tree 네트워크를 사용하였다. 또한 높은 부하에도 충돌을 줄이고 복사망의 성능을 높이기 위해 B-Tree 네트워크의 각 SE에 출력 및 공유 버퍼 성격을 지닌 크로스포인트 버퍼를 추가한 IBBT 네트워크를 제안하였다. 제안된 복사망은 Lee의 복사망의 특성을 유지하며, 이 IBBT 네트워크를 복사망의 BBN에 적용하고, 셀 분할 알고리즘을 사용하여 복사망의 성능을 향상 시켰다.

Decision Tree Techniques with Feature Reduction for Network Anomaly Detection (네트워크 비정상 탐지를 위한 속성 축소를 반영한 의사결정나무 기술)

  • Kang, Koohong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.4
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    • pp.795-805
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    • 2019
  • Recently, there is a growing interest in network anomaly detection technology to tackle unknown attacks. For this purpose, diverse studies using data mining, machine learning, and deep learning have been applied to detect network anomalies. In this paper, we evaluate the decision tree to see its feasibility for network anomaly detection on NSL-KDD data set, which is one of the most popular data mining techniques for classification. In order to handle the over-fitting problem of decision tree, we select 13 features from the original 41 features of the data set using chi-square test, and then model the decision tree using TensorFlow and Scik-Learn, yielding 84% and 70% of binary classification accuracies on the KDDTest+ and KDDTest-21 of NSL-KDD test data set. This result shows 3% and 6% improvements compared to the previous 81% and 64% of binary classification accuracies by decision tree technologies, respectively.