• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.51-61
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• 2012

This paper suggests an algorithm that obtains Directed Graph Minimum Spanning Tree (DMST), using Prim MST algorithm which is Minimum Spanning Tree (MST) of undirected graph. At first, I suggested the Prim DMST algorithm that chooses Minimum Weight Arc(MWA) from out-going nodes from each node, considering differences between undirected graph and directed graph. Next, I proved a disadvantage of Prim DMST algorithm and Chu-Liu/Edmonds DMST (typical representative DMST) of not being able to find DMST, applying them to 3 real graphs. Last, as an algorithm that can always find DMST, an advanced Prim DMST is suggested. The Prim DMST algorithm uses a method of choosing MWA among out-going arcs of each node. On the other hand, the advanced Prim DMST algorithm uses a method of choosing a coinciding arc from the out-going and in-going arcs of each node. And if there is no coinciding arc, it chooses MWA from the out-going arcs from each node. Applying the suggested algorithm to 17 different graphs, it succeeded in finding the same DMST as that found by Chu-Liu/Edmonds DMST algorithm. Also, it does not require such a complicated calculation as that of Chu-Liu/Edmonds DMST algorithm to delete the cycle, and it takes less time for process than Prim DMST algorithm.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1089-1095
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• 2004

The genetic algorithms have been used to take a near optimal solution because The generation of the optimal Steiner tree from a given network is NP-hard problem,. The chromosomes in genetic algorithm are represented with the floating point representation instead of the existing binary string for solving this problem. A spanning tree was obtained from a given network using Prim's algorithm. Then, the new Steiner point was computed using genetic algorithm with the chromosomes in the floating point representation, and it was added to the tree for approaching the result. After repeating these evolving steps, the near optimal Steiner tree was obtained. Using this method, the tree is quickly and exactly approached to the near optimal Steiner tree compared with the existing genetic algorithms using binary string.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.161-169
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• 2012

In general, Euclidean minimum spanning tree is a tree connecting input nodes with minimum connecting cost. But the tree may not be optimal when applied to real world problems of three dimension. In this paper, three dimension Euclidean minimum spanning tree is proposed, connecting all input nodes of 3-dimensional space with minimum cost. In experiments for 30,000 input nodes with 100% space ratio, the tree produced by the proposed method can reduce 90.0% connection cost tree, compared with the tree by two dimension Prim's minimum spanning tree. In two dimension plane, the proposed tree increases 251.2% connecting cost, which is pointless in 3-dimensional real world. Therefore, the proposed method can work well for many connecting problems in real world space of three dimensions.

• The KIPS Transactions:PartA
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• v.17A no.3
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• pp.159-166
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• 2010

In this paper, to obtain the Minimum Spanning Tree (MST) from the graph with several nodes having the same weight, I applied both Bor$\dot{u}$vka and Kruskal MST algorithms. The result came out to such a way that Kruskal MST algorithm succeeded to obtain MST, but not did the Prim MST algorithm. It is also found that an algorithm that chooses Inter-MSF MWE in the $2^{nd}$ stage of Bor$\dot{u}$vka is quite complicating. The $1^{st}$ stage of Bor$\dot{u}$vka has an advantage of obtaining Minimum Spanning Forest (MSF) with the least number of the edges, and on the other hand, Kruskal MST algorithm has an advantage of always obtaining MST though it deals with all the edges. Therefore, this paper suggests an Hybrid MST algorithm which consists of the merits of both Bor$\dot{u}$vka's $1^{st}$ stage and Kruskal MST algorithm. When applied additionally to 6 graphs, Hybrid MST algorithm has a same effect as that of Kruskal MST algorithm. Also, comparing the algorithm performance speed and capacity, Hybrid MST algorithm has shown the greatest performance Therefore, the suggested algorithm can be used as the generalized MST algorithm.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.71-80
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• 2014

Employing PTAS to building minimum spanning tree for a large number of equal distribution input terminal nodes can be a effective way in execution time. But applying PTAS to building minimum spanning tree for tremendous unequal distribution node may lead to performance degradation. In this paper, a partial PTAS reflecting the scheme into specific node dense area is presented. In the environment where 90% of 50,000 input terminal nodes stand close together in specific area, approximate minimum spanning tree by our proposed scheme can show about 88.49% execution time less and 0.86%tree length less than by existing PTAS, and about 87.57%execution time less and 1.18% tree length more than by Prim's naive scheme. Therefore our scheme can go well to many useful applications where a multitude of nodes gathered around specific area should be connected efficiently as soon as possible.

• Journal of KIISE:Information Networking
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• v.34 no.6
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• pp.458-465
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• 2007

Wireless Sensor Network(WSN) is a special network that collects measured data by sensor nodes in the predefined sensor field and forwards them to the base station in a distance using their own routing scheme. WSN requires routing techniques to maximize energy efficiency because sensor nodes have non-rechargeable and thus limited energy. Characteristics of WSN are various according to applications, many of routing algorithms have been proposed. This paper proposes an algorithm called A-PEGASIS that basically bases on PEGASIS and enhances in two aspects - an elegant chain generation algorithm and periodical update of chains. We compare performance of the previous algorithm of LEACH, PEGASIS, PEDAP and PEDAP-PA with ours through simulation. It confirms that the A-PEGASIS is most superior in terms of average WSN lifetime and high probability of node survival rate during WSN life time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.165-173
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• 2012

Given a connected, weighted, and undirected graph, the Minimum Spanning Tree (MST) should have minimum sum of weights, connected all vertices, and without any cycle taking place. Borůvka Algorithm is firstly suggested as an algorithm to evaluate the MST, but it is not widely used rather than Prim and Kruskal algorithms. Borůvka algorithm selects the Minimum Weight Edge (MWE) from each vertex with distinct weights in $1^{st}$ stage, and selects the MWE from each MSF (Minimum Spanning Forest) in $2^{nd}$ stage. But the cycle check and the number of MSF in $1^{st}$ stage and $2^{nd}$ stage are difficult to implication by computer program even if it is easy to verify visually. This paper suggests the generalized Borůvka Algorithm, This algorithm selects all of the same MWEs for each vertex, then checks the cycle and constructs MSF for ascending sorted MWEs. Kruskal method bring into this process. if the number of MSF greats then 1, this algorithm selects MWE from ascending sorted inter-MSF edges. The generalized Borůvka algorithm is verified its application by being applied to the 7 graphs with the many minimum weights or distinct weight edges for any vertex. As a result, the generalized Borůvka algorithm is less required for cycle verification then the Kruskal algorithm. Therefore, the generalized Borůvka algorithm is more fast to obtain MST then Kruskal algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1188-1191
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• 2011

IPTV 방송에서 인터넷 기반 멀티캐스트는 일대다 또는 다대다 통신을 위한 차세대 중요한 서비스로 주목 받고 있다. 멀티캐스트는 네트워크 또는 애플리케이션 레벨에서 서비스할 수 있다. IP 멀티캐스트는 소스노드에서 라우터로 데이터그램을 보내면 라우터가 이를 복제하여 수신노드들에게 전달해 주는 네트워크레벨 서비스로 네트워크 자원을 효율적 사용할 수 있다. 그러나 네트워크에 IP 멀티캐스트 라우터가 설치되어야 하는 등 여러 문제로 인해 널리 사용되지 못하고 있다. 따라서 대안으로 애플리케이션 레벨에서의 오버레이 멀티캐스트가 주목 받고 있다. 오버레이 멀티캐스트는 종단호스트가 라우터처럼 동작하는 것으로 비록 IP 멀티캐스트에 비해서 링크 사용율과 지연 값이 높아질 수 있지만, IP 멀티캐스트의 현실적인 적용의 어려움을 해결할 수 있는 장점을 가지고 있다. 본 논문에서는 IP 멀티캐스트가 제공되지 않는 네트워크에서 효율적인 SVC(Scalable Video Coding) 멀티미디어 방송서비스와 SSENS(SVC Stream Exchange Network Server) 라우팅을 위한 MST(Minimum Spanning tree)를 목적으로 하는 오버레이 멀티캐스트 트리를 구현하는 알고리즘을 설계한다. 제안된 알고리즘의 성능 분석을 위해 시뮬레이션을 통해 패킷 손실 측면에서 Prim 알고리즘에 비해 평균 패킷 손실율이 40% 가까이 향상됨을 증명하였다.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.55-61
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• 2021

As the demand for distance education increases, it is necessary to present a problem solving path through a learning tracking algorithm in order to support the efficient learning of learners. In this paper, we proposed a problem solving path of various difficulty levels in various subjects by supplementing the existing learning tracking algorithm. Through the data set obtained through the path for solving the learner's problem, the path through the prim's minimum Spanning tree was secured, and the optimal problem solving path through the recursive neural network was suggested through the path data set. As a result of the performance evaluation of the contents proposed in this paper, it was confirmed that more than 52% of the test subjects included the problem solving path suggested in the problem solving process, and the problem solving time was also improved by more than 45%.