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

• Journal of the Korean Operations Research and Management Science Society
• /
• v.33 no.3
• /
• pp.17-28
• /
• 2008

The Steiner arborescence problem is known to be NP-hard. The objective of this problem is to find a minimal Steiner tree which starts from a designated node and spans all given terminal nodes. This paper proposes a method based on a two-step procedure to solve this problem efficiently. In the first step, graph reduction rules eliminate useless nodes and arcs which do not contribute to make an optimal solution. In the second step. ant colony algorithm with use of Prim's algorithm is used to solve the Steiner arborescence problem in the reduced graph. The proposed method based on a two-step procedure is tested in the five test problems. The results show that this method finds the optimal solutions to the tested problems within 50 seconds. The algorithm can be applied to undirected Steiner tree problems with minor changes. 18 problems taken from Beasley are used to compare the performances of the proposed algorithm and Singh et al.'s algorithm. The results show that the proposed algorithm generates better solutions than the algorithm compared.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.3 no.6
• /
• pp.612-627
• /
• 2009

The high-level contribution of this paper is to illustrate the effectiveness of using graph theory tree traversal algorithms (pre-order, in-order and post-order traversals) to generate the chain of sensor nodes in the classical Power Efficient-Gathering in Sensor Information Systems (PEGASIS) data aggregation protocol for wireless sensor networks. We first construct an undirected minimum-weight spanning tree (ud-MST) on a complete sensor network graph, wherein the weight of each edge is the Euclidean distance between the constituent nodes of the edge. A Breadth-First-Search of the ud-MST, starting with the node located closest to the center of the network, is now conducted to iteratively construct a rooted directed minimum-weight spanning tree (rd-MST). The three tree traversal algorithms are then executed on the rd-MST and the node sequence resulting from each of the traversals is used as the chain of nodes for the PEGASIS protocol. Simulation studies on PEGASIS conducted for both TDMA and CDMA systems illustrate that using the chain of nodes generated from the tree traversal algorithms, the node lifetime can improve as large as by 19%-30% and at the same time, the energy loss per node can be 19%-35% lower than that obtained with the currently used distance-based greedy heuristic.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.9
• /
• pp.3598-3614
• /
• 2020

With the increase of motor vehicles and tourism demand, some traffic problems gradually appear, such as traffic congestion, safety accidents and insufficient allocation of traffic resources. Facing these challenges, a model of Spatio-Temporal Dilated Convolutional Network (STDGCN) is proposed for assistance of extracting highly nonlinear and complex characteristics to accurately predict the future traffic flow. In particular, we model the traffic as undirected graphs, on which graph convolutions are built to extract spatial feature informations. Furthermore, a dilated convolution is deployed into graph convolution for capturing multi-scale contextual messages. The proposed STDGCN integrates the dilated convolution into the graph convolution, which realizes the extraction of the spatial and temporal characteristics of traffic flow data, as well as features of road occupancy. To observe the performance of the proposed model, we compare with it with four rivals. We also employ four indicators for evaluation. The experimental results show STDGCN's effectiveness. The prediction accuracy is improved by 17% in comparison with the traditional prediction methods on various real-world traffic datasets.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.12
• /
• pp.1225-1230
• /
• 2014

This paper investigates the group average-consensus and group formation-consensus problems for first-order multi-agent systems. The control protocol for group consensus is designed by considering the positive adjacency elements. Since each intra-group Laplacian matrix cannot be satisfied with the in-degree balance because of the positive adjacency elements between groups, we decompose the Laplacian matrix into an intra-group Laplacian matrix and an inter-group Laplacian matrix. Moreover, average matrices are used in the control protocol to analyze the stability of multi-agent systems with a fixed and undirected communication topology. Using the graph theory and the Lyapunov functional, stability analysis is performed for group average-consensus and group formation-consensus, respectively. Finally, some simulation results are presented to validate the effectiveness of the proposed control protocol for group consensus.

• Korean Management Science Review
• /
• v.29 no.1
• /
• pp.153-168
• /
• 2012

Order allocation is one of the most important decision-making problems of firms having significant influences on performances of themselves and the whole supply chain. Existing researches about order allocation have mainly focused on evaluating capabilities of directly connected suppliers so that it is hard to consider effects and interactions from undirected connections over multiple lower-layers. To alleviate the limitation, this paper proposed a novel approach to order allocation using structural hole. By applying the concept of structural hole to the supply network, we could evaluate the structural supplying powers of firms with respect to both of direct and indirect connections. In the proposed approach, we derived a methodology to measure the potential supplying power of each firm by modifying the effective size as one of the measurements of structural hole and then, proposed its application, the structural hole based order allocation strategy. Furthermore, we conducted the agent based modeling of supply chain to perform the decision-making process of order allocation and simulated the proposed strategy. As a results, by coping with the variance of demand more stably, it could improve the performance of supply chain from the aspects of fill rate, inventory level and demand-supply balance.

• Journal of Broadcast Engineering
• /
• v.25 no.5
• /
• pp.808-811
• /
• 2020

This paper proposes a method to minimize the error of the Kinect camera sensor by using a random undirected Kalman filter. Kinect cameras, which provide RGB values and depth information, cause nonlinear errors in the sensor, causing problems in various applications such as skeleton detection. Conventional methods have tried to remove errors by using various filtering techniques. However, there is a limit to removing nonlinear noise effectively. Therefore, in this paper, a randomized unscented Kalman filter was applied to predict and update the nonlinear noise characteristics, we next tried to enhance a performance of skeleton detection. The experimental results confirmed that the proposed method is superior to the conventional method in quantitative results and reconstructed images on 3D space.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.23 no.1
• /
• pp.25-33
• /
• 2013

The floating offshore wind turbines are usually exposed to the wave and wind excitations which are irregular and undirected. In this paper, the sloshing characteristics of annular cylindrical tank were experimentally investigated to reduce the structural dynamic motion of floating offshore wind turbine which is robust to the irregular change of excitation direction of wind and wave. The formula for the natural sloshing frequencies of this annular cylindrical tank was derived theoretically. In order to validate this formula, the shaking equipment was established and frequency response functions were measured. Two types of tank were considered. The first and second natural sloshing frequencies were investigated according to the depth of the water. It has been observed that between theoretical and experimental results shows a good agreement.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.4
• /
• pp.47-60
• /
• 2015

In this paper, we propose a simple and useful method using a port role to visualize the network attacks. The port role defines the behavior of the port from the source and destination port number of network session. Based on the port role, the port provides the brief security features of each node as an attacker, a victim, a server, and a normal host. We have automatically classified and identified the type of node based on the port role and security features. We detected and visualized the network attacks using these features of the node by the port role. In addition, we are intended to solve the problems with existing visualization technologies which are the reflection problem caused an undirected network session and the problem caused decreasing of distinct appearance when occurs a large amount of the sessions. The proposed method monitors anomalies occurring in an entire network and displays detailed information of the attacker, victim, server, and hosts. In addition, by providing a categorized analysis of network attacks, this method can more precisely detect and distinguish them from normal sessions.

• Journal of KIISE:Computer Systems and Theory
• /
• v.26 no.10
• /
• pp.1258-1263
• /
• 1999

본 논문에서는 CRCW(Concurrent Read Concurrent Write)와 CREW(Concurrent Read Exclusive Write) PRAM(Parallel Random Access Machine) 모델에서 무방향성 그래프 G=(V, E)의 극대 매칭을 구하기 위해 간결한 랜덤 병렬 알고리즘을 제안한다. CRCW PRAM 모델에서 m개의 선을 가진 그래프에 대해, 제안된 매칭 알고리즘은 m개의 프로세서 상에서 {{{{ OMICRON (log m)의 기대 수행 시간을 가진다. 또한 CRCW 알고리즘을 CREW PRAM 모델에서 구현한 CREW 알고리즘은 OMICRON (log^2 m)의 기대 수행 시간을 가지지만,OMICRON (m/logm) 개의 프로세서만을 가지고 수행될 수 있다.Abstract This paper presents simple randomized parallel algorithms for finding a maximal matching in an undirected graph G=(V, E) for the CRCW and CREW PRAM models. The algorithm for the CRCW model has {{{{ OMICRON (log m) expected running time using m processors, where m is the number of edges in G We also show that the CRCW algorithm can be implemented on a CREW PRAM. The CREW algorithm runs in {{{{ OMICRON (log^2 m) expected time, but it requires only OMICRON (m / log m) processors.