• Title/Summary/Keyword: tree network

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aCN-RB-tree: Constrained Network-Based Index for Spatio-Temporal Aggregation of Moving Object Trajectory

  • Lee, Dong-Wook;Baek, Sung-Ha;Bae, Hae-Young
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.3 no.5
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    • pp.527-547
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    • 2009
  • Moving object management is widely used in traffic, logistic and data mining applications in ubiquitous environments. It is required to analyze spatio-temporal data and trajectories for moving object management. In this paper, we proposed a novel index structure for spatio-temporal aggregation of trajectory in a constrained network, named aCN-RB-tree. It manages aggregation values of trajectories using a constraint network-based index and it also supports direction of trajectory. An aCN-RB-tree consists of an aR-tree in its center and an extended B-tree. In this structure, an aR-tree is similar to a Min/Max R-tree, which stores the child nodes' max aggregation value in the parent node. Also, the proposed index structure is based on a constrained network structure such as a FNR-tree, so that it can decrease the dead space of index nodes. Each leaf node of an aR-tree has an extended B-tree which can store timestamp-based aggregation values. As it considers the direction of trajectory, the extended B-tree has a structure with direction. So this kind of aCN-RB-tree index can support efficient search for trajectory and traffic zone. The aCN-RB-tree can find a moving object trajectory in a given time interval efficiently. It can support traffic management systems and mining systems in ubiquitous environments.

Preconfigured Multicast Delivery Tree in Mobile IP (Mobile IP에서 기설정된 전달 트리를 이용한 멀티캐스팅 방안)

  • C.B. Chun;C.H. Kang;Lee, J.H.;Kwon, K.H.;Kim, B.S.;Hong, J.P.
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10e
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    • pp.76-78
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    • 2002
  • Multicasting over mobile IP network becomes more important with the increasing needs of supporting multimedia services in mobile network. The IETF has suggested two approaches which are remote subscription and bidirectional tunneling for supporting mobility management in multicasting over mobile IP. But these protocols have problems - the frequent reconstruction of multicast delivery tree, packet less during handoff, convergence problem, and so on. In this paper, we propose to use preconfiguration of multicast delivery tree when mobile host enters the foreign network. It will decrease the frequency of multicast delivery tree reconstruction, and reduce the packet loss during handoff, Also the multicast delivery tree maintained by Keep Alive messages makes the signaling overload of networks diminished.

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Hybridized Decision Tree methods for Detecting Generic Attack on Ciphertext

  • Alsariera, Yazan Ahmad
    • International Journal of Computer Science & Network Security
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    • v.21 no.7
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    • pp.56-62
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    • 2021
  • The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.

A New Tree Representation for Evolutionary Algorithms (진화 알고리듬을 위한 새로운 트리 표현 방법)

  • Soak, Sang-Moon;Ahn, Byung-Ha
    • Journal of Korean Institute of Industrial Engineers
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    • v.31 no.1
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    • pp.10-19
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    • 2005
  • The minimum spanning tree (MST) problem is one of the traditional optimization problems. Unlike the MST, the degree constrained minimum spanning tree (DCMST) of a graph cannot, in general, be found using a polynomial time algorithm. So, finding the DCMST of a graph is a well-known NP-hard problem of importance in communications network design, road network design and other network-related problems. So, it seems to be natural to use evolutionary algorithms for solving DCMST. Especially, when applying an evolutionary algorithm to spanning tree problems, a representation and search operators should be considered simultaneously. This paper introduces a new tree representation scheme and a genetic operator for solving combinatorial tree problem using evolutionary algorithms. We performed empirical comparisons with other tree representations on several test instances and could confirm that the proposed method is superior to other tree representations. Even it is superior to edge set representation which is known as the best algorithm.

Classification of Surface Defects on Cold Rolled Strip by Tree-Structured Neural Networks (트리구조 신경망을 이용한 냉연 강판 표면 결함의 분류)

  • Moon, Chang-In;Choi, Se-Ho;Kim, Gi-Bum;Joo, Won-Jong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.6 s.261
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    • pp.651-658
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    • 2007
  • A new tree-structured neural network classifier is proposed for the automatic real-time inspection of cold-rolled steel strip surface defects. The defects are classified into 3 groups such as area type, disk type, area & line type in the first stage of the tree-structured neural network. The defects are classified in more detail into 11 major defect types which are considered as serious defects in the second stage of neural network. The tree-structured neural network classifier consists of 4 different neural networks and optimum features are selected for each neural network classifier by using SFFS algorithm and correlation test. The developed classifier demonstrates very plausible result which is compatible with commercial products having high world-wide market shares.

Network Architecture and Routing Protocol for Supporting Mobile IP in Mobile Ad Hoc Networks (이동 애드 혹 네트워크의 Mobile IP 지원을 위한 네트워크 구조 및 라우팅 프로토콜)

  • Oh, Hoon;TanPhan, Anh
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.1A
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    • pp.24-35
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    • 2008
  • We propose a tree-based integrated network of infrastructure network and mobile ad hoc network to effectively support Mobile IP for mobile ad hoc networks and also proposed a network management protocol for formation and management of the integrated network and a tree-based routing protocol suitable for the integrated network. The integrated network has fixed gateways(IGs) that connect two hybrid networks and the mobile nodes in the network form a small sized trees based on the mobile nodes that are in the communication distance with a IG. A new node joins an arbitrary tree and is registered with its HA and FA along tree path. In addition, the proposed protocol establishes a route efficiently by using the tree information managed in every node. We examined the effectiveness of the tree-based integrated network for some possible network deployment scenarios and compared our routing protocol against the Mobile IP supported AODV protocol.

Multicast Tree Generation using Meta Reinforcement Learning in SDN-based Smart Network Platforms

  • Chae, Jihun;Kim, Namgi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.9
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    • pp.3138-3150
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    • 2021
  • Multimedia services on the Internet are continuously increasing. Accordingly, the demand for a technology for efficiently delivering multimedia traffic is also constantly increasing. The multicast technique, that delivers the same content to several destinations, is constantly being developed. This technique delivers a content from a source to all destinations through the multicast tree. The multicast tree with low cost increases the utilization of network resources. However, the finding of the optimal multicast tree that has the minimum link costs is very difficult and its calculation complexity is the same as the complexity of the Steiner tree calculation which is NP-complete. Therefore, we need an effective way to obtain a multicast tree with low cost and less calculation time on SDN-based smart network platforms. In this paper, we propose a new multicast tree generation algorithm which produces a multicast tree using an agent trained by model-based meta reinforcement learning. Experiments verified that the proposed algorithm generated multicast trees in less time compared with existing approximation algorithms. It produced multicast trees with low cost in a dynamic network environment compared with the previous DQN-based algorithm.

Tree-based Multi-channel Communication with Interference Avoidance using Dynamic Channel Switching in Wireless Sensor Network

  • Mohd, Noor Islam;Choi, Sun-Woong;Jang, Yeong-Min
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.12B
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    • pp.1498-1505
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    • 2009
  • In centralized control sensor network, tree-based multi-channel communication overcomes the recurrent channel switching and makes possible to transfer data simultaneously from different sources. In our paper, we propose a greedy algorithm named as NIT (Non-Intersecting Tree) that the trees can avoid inter-tree interference. We also propose channel switching technique by which trees can avoid link failure or area blocking due to external interference locally without rerunningthe algorithm and without interrupting the whole network. At first we applied our algorithm for a random topology and then we evaluate the performance of the network using NS-2 simulator. The results show that with the increasing of channel the throughputand delivery ratio are increased significantly. We got better performance than a using a recent proposed Tree-based Multi-Channel Protocol (TMCP).

A Design of Efficient Cluster Sensor Network Using Approximate Steiner Minimum Tree (근사 최소 스타이너 트리를 이용한 효율적인 클러스터 센서 네트워크의 구성)

  • Kim, In-Bum
    • The KIPS Transactions:PartA
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    • v.17A no.2
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    • pp.103-112
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    • 2010
  • Cluster sensor network is a sensor network where input nodes crowd densely around some nuclei. Steiner minimum tree is a tree connecting all input nodes with introducing some additional nodes called Steiner points. This paper proposes a mechanism for efficient construction of a cluster sensor network connecting all sensor nodes and base stations using connections between nodes in each belonged cluster and between every cluster, and using repetitive constructions of approximate Steiner minimum trees. In experiments, while taking 1170.5% percentages more time to build cluster sensor network than the method of Euclidian minimum spanning tree, the proposed mechanism whose time complexity is O($N^2$) could spend only 20.3 percentages more time for building 0.1% added length network in comparison with the method of Euclidian minimum spanning tree. The mechanism could curtail the built trees' average length by maximum 3.7 percentages and by average 1.9 percentages, compared with the average length of trees built by Euclidian minimum spanning tree method.

Scheduling Computational Loads in Single Level Tree Network

  • Cui, Run;Sundaram, Suresh;Kim, Hyoung-Joong
    • 한국정보통신설비학회:학술대회논문집
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    • 2009.08a
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    • pp.131-135
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    • 2009
  • This paper is the introduction of our work on distributed load scheduling in single-level tree network. In this paper, we derive a new calculation model in single-level tree network and show a closed-form formulation of the time for computation system. There are so many examples of the application of this technology such as distributed database, biology computation on genus, grid computing, numerical computing, video and audio signal processing, etc.

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