• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.25
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• pp.83-90
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• 1992

This paper aims at the problem that design the network of Rig-star type with the minimum cost, which the Ring is composed of the selected nodes(concentrators) among the several candidate nodes on the network and other nodes(terminals) is connected to the Ring by star subnetwork. Especially, we consider the terminal reliability in network design problem. We develop the heuristic algorithm for network design problem to obtain the near optimal(best) solution for problem. We use an add-heuristic method and 2-exchange method in developing the heuristic algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.2
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• pp.129-138
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• 2003

The traveling salesman problem (TSP) is an NP-hard problem. As the number of nodes increases, it takes a lot of time to find an optimal solution. Instead of considering all arcs, if we select and consider only some arcs more likely to be included in an optimal solution, we can find efficiently an optimal solution. Arc candidate set is a group of some good arcs. For the Lack of study in the asymmetric TSP. it needs to research arc candidate set for the asymmetric TSP systematically. In this paper, we suggest a regression function determining arc candidate set for the asymmetric TSP. We established the function based on 2100 experiments, and we proved the goodness of fit for the model through various 787problems. The result showed that the optimal solutions obtained from our arc candidate set are equal to the ones of original problems. We expect that this function would be very useful to reduce the complexity of TSP.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.332-337
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• 2016

The rapid reconstruction of a transfer path is caused by frequent secession of nodes in many applications using overlay multicast. For this, however, many studies have been proposed, but a study of fast path recovery is required. This paper proposes a new method for fast path recovery to improve the path reconstruction time and for stable path maintain caused by the sudden secession of the parent node on overlay multicast. The proposed method uses the virtual transfer path and the candidate parent node for the fast path recovery. All nodes exchange periodically the RTT (Round Trip Time) information between the other nodes of similar position itself and neighboring node. All nodes have a candidate parent node list, and each node stores the exchanged RTT information on the list. Each node constructs the virtual transfer path to reduce the recovery time after deciding a candidate parent node that is one of them by the RTT order. In this way, when the parent node is seceded, all nodes can recover the transfer path quickly using the virtual transfer path. The simulation result showed that the recovery time of the proposed method is an average 30% faster than the known method.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.3-5
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• 2006

Recent advances in the internet infrastructure have resulted in a large number of huge Web sites and portals worldwide. These Web sites are being visited by various types of users in many different ways. Among all the web page access sequences from different users, some of them occur so frequently that may need an attention from those who are interested. We call them frequent access patterns and access sequences that can be frequent the candidate patterns. Since these candidate patterns play an important role in the incremental Web mining, it is important to efficiently generate, add, delete, and search for them. This thesis presents a novel tree structure that can efficiently store the candidate patterns and a related set of algorithms for generating the tree structure adding new patterns, deleting unnecessary patterns, and searching for the needed ones. The proposed tree structure has a kind of the 3 dimensional link structure and its nodes are layered.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.156-160
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• 2005

We introduce a fully automatic clustering method to classier candidate paralog clusters from a set of protein sequences within one genome. A set of protein sequences is represented as a set of nodes, each represented by the amino acid sequence for a protein with the sequence similarities among them constituting a set of edges in a graph of protein relationships. We use graph-based clustering methods to identify structurally consistent sets of nodes which are strongly connected with each other. Our results are consistent with those from current leading systems such as COG/KOG and KEGG based on manual curation. All the results are viewable at http://www.cs.rutgers.edu/${\sim}$seabee.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.577-582
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• 2008

In this paper, we present a scheme to overcome the worst case complexity of the sphere decoder. If the number of visited nodes reaches the threshold, the detected symbol vector is determined between two candidate symbol vectors. One candidate symbol vector is obtained from the demodulated output of ZF receiver which is initial stage of the sphere decoder. The other candidate symbol vector consists of two sub-symbol vectors. The first sub-symbol vector consists of lately visited nodes running from the most upper layer. The second one contains corresponding demodulated outputs of ZF receiver. Between these two candidate symbol vectors, the one with smaller euclidean distance to the received symbol vector is chosen as detected symbol vector. In addition, we show the upper bound of symbol error rate performance for the sphere decoder using the proposed scheme. In the simulation, the proposed scheme shows the significant reduction of the worst case complexity while having negligible SER performance degradation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2764-2782
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• 2021

Existing city-level boundary nodes identification methods need to locate all IP addresses on the path to differentiate which IP is the boundary node. However, these methods are susceptible to time-delay, the accuracy of location information and other factors, and the resource consumption of locating all IPes is tremendous. To improve the recognition rate and reduce the locating cost, this paper proposes an algorithm for city-level boundary node identification based on bidirectional approaching. Different from the existing methods based on time-delay information and location results, the proposed algorithm uses topological analysis to construct a set of candidate boundary nodes and then identifies the boundary nodes. The proposed algorithm can identify the boundary of the target city network without high-precision location information and dramatically reduces resource consumption compared with the traditional algorithm. Meanwhile, it can label some errors in the existing IP address database. Based on 45,182,326 measurement results from Zhengzhou, Chengdu and Hangzhou in China and New York, Los Angeles and Dallas in the United States, the experimental results show that: The algorithm can accurately identify the city boundary nodes using only 20.33% location resources, and more than 80.29% of the boundary nodes can be mined with a precision of more than 70.73%.

• ETRI Journal
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• v.40 no.2
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• pp.237-245
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• 2018

The Distributed Modulated Wideband Converter (DMWC) is a networking system developed from the Modulated Wideband Converter, which converts all sampling channels into sensing nodes with number variables to implement signal undersampling. When the number of sparse subbands changes, the number of nodes can be adjusted flexibly to improve the reconstruction rate. Owing to the different attenuations of distributed nodes in different locations, it is worthwhile to find out how to select the optimal sensing node as the sampling channel. This paper proposes the spectrum sensing of DMWC based on a Markov random field (MRF) to select the ideal node, which is compared to the image edge segmentation. The attenuation of the candidate nodes is estimated based on the attenuation of the neighboring nodes that have participated in the DMWC system. Theoretical analysis and numerical simulations show that neighboring attenuation plays an important role in determining the node selection, and selecting the node using MRF can avoid serious transmission attenuation. Furthermore, DMWC can greatly improve recovery performance by using a Markov random field compared with random selection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1128-1137
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• 2012

In this paper, we propose an improved MPR selection method considering mobility and density of nodes for ad-hoc networks. In Optimized Link State Routing(OLSR), a node selects 1-hop Multi-Point Relay(MPR) nodes to cover all 2-hop neighbor nodes. In a high population area, many nodes are likely to be selected as MPR nodes by their neighbors. This leads to increase in contention among MPR nodes and may decrease overall performance of the network. In addition, when an MPR node leaves the communication range of its MPR selector node, it can no longer perform as the MPR node and the performance of the network may also decrease. In this paper, we propose an MPR selection method which measures the mobility and density of nodes by exchanging the hello messages and gives the priorities to the nodes for MPR selection. Performance evaluation results using OPNET show that the proposed method is superior to OLSR or the MPR candidate method in terms of connectivity and throughput.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.164-172
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• 2013

We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.