• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.184-193
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• 1994

This paper considers the Updating Minimum-weight Spanning Tree Problem(UMP), that is, the problem to update the Minimum-weight Spanning Tree(MST) in response to topology change of the network. This paper proposes the algorithm which reconstructs the MST after several links deleted and added. Its message complexity and its ideal-time complexity are Ο(m＋n log(t＋f)) and Ο(n＋n log(t＋f)) respectively, where n is the number of processors in the network, t(resp.f) is the number of added links (resp. the number of deleted links of the old MST), And m=t＋n if f=Ο, m=e (i.e. the number of links in the network after the topology change) otherwise. Moreover the last part of this paper touches in the algorithm which deals with deletion and addition of processors as well as links.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.472-478
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• 2017

In this paper, we deals with optimizing traffic signal timing in grid networks by using a network topology design method. Optimizing traffic signal timing includes minimizing delay time delay between departure and destination by interlocking straight traffic signal in the minimum spanning tree(MST). On the assumption that users of network abide by the paths provided in this paper, this paper shows optimizing traffic signal timing in grid networks. the paths provided in this paper is gathered by using Dijkstra algorithm used in computer networks. The results indicate minimizing delay time of passing through the grid network and interlocking traffic signal in the grid network.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.31-39
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• 2015

The degree-constrained minimum spanning tree (d-MST) problem is considered NP-complete for no exact solution-yielding polynomial algorithm has been proposed to. One thus has to resort to an heuristic approximate algorithm to obtain an optimal solution to this problem. This paper therefore presents a polynomial time algorithm which obtains an intial solution to the d-MST with the help of Kruskal's algorithm and performs k-opt on the initial solution obtained so as to derive the final optimal solution. When tested on 4 graphs, the algorithm has successfully obtained the optimal solutions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.233-241
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• 2014

This paper suggests a fast minimum spanning tree algorithm which simplify the original graph to 2-edge connected graph, and using the cycling property. Borůvka algorithm firstly gets the partial spanning tree using cycle property for one-edge connected graph that selects the only one minimum weighted edge (e) per vertex (v). Additionally, that selects minimum weighted edge between partial spanning trees using cut property. Kruskal algorithm uses cut property for ascending ordered of all edges. Reverse-delete algorithm uses cycle property for descending ordered of all edges. Borůvka and Kruskal algorithms always perform |e| times for all edges. The proposed algorithm obtains 2-edge connected graph that selects 2 minimum weighted edges for each vertex firstly. Secondly, we use cycle property for 2-edges connected graph, and stop the algorithm until |e|=|v|-1 For actual 10 benchmark data, The proposed algorithm can be get the minimum spanning trees. Also, this algorithm reduces 60% of the trial number than Borůvka, Kruskal and Reverse-delete algorithms.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.227-247
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• 2018

For intermittently connected wireless sensor networks deployed in hash environments, sensor nodes may fail due to internal or external reasons at any time. In the process of data collection and recovery, we need to speed up as much as possible so that all the sensory data can be restored by accessing as few survivors as possible. In this paper a novel redundant data storage algorithm based on minimum spanning tree and quasi-randomized matrix-QRNCDS is proposed. QRNCDS disseminates k source data packets to n sensor nodes in the network (n>k) according to the minimum spanning tree traversal mechanism. Every node stores only one encoded data packet in its storage which is the XOR result of the received source data packets in accordance with the quasi-randomized matrix theory. The algorithm adopts the minimum spanning tree traversal rule to reduce the complexity of the traversal message of the source packets. In order to solve the problem that some source packets cannot be restored if the random matrix is not full column rank, the semi-randomized network coding method is used in QRNCDS. Each source node only needs to store its own source data packet, and the storage nodes choose to receive or not. In the decoding phase, Gaussian Elimination and Belief Propagation are combined to improve the probability and efficiency of data decoding. As a result, part of the source data can be recovered in the case of semi-random matrix without full column rank. The simulation results show that QRNCDS has lower energy consumption, higher data collection efficiency, higher decoding efficiency, smaller data storage redundancy and larger network fault tolerance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.51-59
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• 2014

This paper suggests a method of lessening number of a graph's edges population in order to rapidly obtain the minimum spanning tree. The present minimum spanning tree algorithm works on all the edges of the graph. However, the suggested algorithm reduces the edges population size by means of applying a method of deleting maximum weight edges in advance from vertices with more than 2 valencies. Next, it applies a stopping criterion which ideally terminates Borůvka, Prim, Kruskal and Reverse-Delete algorithms for reduced edges population. On applying the suggested algorithm to 9 graphs, it was able to minimize averagely 83% of the edges that do not become MST. In addition, comparing to the original graph, edges are turned out to be lessened 38% by Borůvka, 37% by Prim, 39% by Kruskal and 73% by Reverse-Delete algorithm, and thereby the minimum spanning tree is obtained promptly.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.159-171
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• 2011

This paper suggests an algorithm that obtains the Minimum Spanning Tree for directed graph (DMST). The existing Chu-Liu/Edmonds DMST algorithm has chances of the algorithm not being able to find DMST or of the sum of ST not being the least. The suggested algorithm is made in such a way that it always finds DMST, rectifying the disadvantage of Chu-Liu/Edmonds DMST algorithm. Firstly, it chooses the Minimum-Weight Arc (MWA) from all the nodes including a root node, and gets rid of the nodes in which cycle occurs after sorting them in an ascending order. In this process, Minimum Spanning Forest (MST) is obtained. If there is only one MSF, DMST is obtained. And if there are more than 2 MSFs, to determine MWA among all MST nodes, it chooses a method of directly calculating the sum of all the weights, and hence simplifies the emendation process for solving a cycle problem of Chu-Liu/Edmonds DMST algorithm. The suggested Sulee DMST algorithm can always obtain DMST that minimizes the weight of the arcs no matter if the root node is set or not, and it is also capable to find the root node of a graph with minimized weight.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.809-812
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• 2008

통신 시스템에 대한 관심은 인터넷의 급격한 발전에 의해 가상공간의 출현과 유비쿼터스 컴퓨팅 환경 구축에 대한 요구가 증대됨에 따라 관련 이론 및 기술의 발전을 주도해 왔다. 이와 관련하여 가장 근간이 되는 문제들 중 하나는 최적 정보 통신 스패닝 트리 (OCST: Optimal Communication Spanning Tree) 설계 문제이다. 본 논문에서는 이러한 OCST 설계 문제를 네트워크 신뢰도를 고려하여 해결하기 위해 유전 알고리즘 (GA)를 이용한다. 본 논문에서는 유전 알고리즘을 이용함에 있어서 n개의 노드들로 구성된 네트워크 문제에서 n-2개의 숫자열로 표현 가능한 유전자 표현법을 이용하고 신뢰성 있는 OCST 설계 문제 해결을 위한 해법으로서 유전 알고리즘을 제안한다. 임의로 생성된 예제에 대한 수치 실험을 통해 통신시스템의 기본 문제 중 하나인 OCST 설계 문제의 해법으로서의 제안 알고리즘의 유용성과 효율성을 확인한다.

• 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.