• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.4
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• pp.59-70
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• 2003

Spatial data base system provides many query types and most of them are required frequent disk I/O and much CPU time. k-NN search is to find k-th closest object from the query point and up to now, several k-NN search methods have been proposed. Among these, MINMAX distance method has an aim not to access unnecessary node by adapting pruning technique. But this method accesses more disks than necessary while pruning unnecessary nodes. In this paper, we propose new k-NN search algorithm based on density of object. With this method, we predict the radius to be expected to contain k-NN objects using density of data set and search those objects within this radius and then adjust radius if failed. Experimental results show that this method outperforms the previous MINMAX distance method. This algorithm visit less disks than MINMAX method by the factor of maximum 22% and average 7%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2221-2229
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• 2006

Optimal path search algorithm which is a killer application of mobile device to utilize location information should consider traffic flows of the roads as well as the distance between a departure and destination. The existing path search algorithms, however, are net able to cope efficiently with the change of the traffic flows. In this paper, we propose a new optimal path search algorithm. The algorithm takes the current flows into consideration in order to reduce the cost to get destination. It decomposes the road network into Fixed Grid to get variable heuristics. We also carry out the experiments with Dijkstra and Ar algorithm in terms of the execution time, the number of node accesses and the accuracy of path. The results obtained from the experimental tests show the proposed algorithm outperforms the others. The algorithm is highly expected to be useful in a advanced telematics systems.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.209-220
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• 2017

As a semantic data is widely used in various applications such as Knowledge Bases and Semantic Web, needs for effective search over a large amount of RDF data have been increasing. Previous keyword search methods based on distinct root semantics only retrieve a set of answer trees having different root nodes. Thus, they often find answer trees with similar meanings or low query relevance together while those with the same root node cannot be retrieved together even if they have different meanings and high query relevance. We propose a new method to find diverse and relevant answers to the query by permitting duplication of root nodes among them. We present an efficient query processing algorithm using path indexes to find top-k answers given a maximum amount of root duplication a set of answer trees can have. We show by experiments using a real dataset that the proposed approach can produce effective answer trees which are less redundant in their content nodes and more relevant to the query than the previous method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.4
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• pp.467-478
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• 2016

In this paper, we try to find the optimal locations of NeNB(Nomadic evolved NodeB)s for maximizing the overall throughput of the PS-LTE networks. Since finding optimal locations of all NeNBs in a given area is NP-hard(Non-deterministic Polynomial time-hard) problem, we proposed a PSO-based heuristic approach. In order to evaluate the performance, we conducted two experiments. We compared performance with other schemes such as Exhaustive Search, Random Walk Search, and locating neighboring NeNBs with the same NeNB-to-NeNB distance. The proposed method showed the similar results to the exhaustive search method in terms of locating optimal position and user's data throughput. The proposed method, however, has the fast and consistent convergence time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.137-141
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• 2005

Optimal path search algorithm should consider traffic flows of the roads as well as the distance between a departure and destination, The existing path search algorithms, however, usually don't apply the continuously changed traffic flows. In this paper, we propose a new optimal path search algorithm. the algorithm takes the current flows into consideration in order to reduce the cost to get destination. It decomposes the road networks into Fixed Grid to get variable heuristics. We also carry out the experiments with Dijkstra and $A^*$ algorithm in terms of the execution time, the number of node accesses and the accuracy of path. The results obtained from the experimental tests show the proposed algorithm outperforms the others. The algorithm is highly expected to be useful in a advanced telematics systems.

• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.406-412
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• 2001

IP address lookup is to determine the next hop destination of an incoming packet in the router. The address lookup is a major bottleneck in high performance router due to the increased routing table sizes, increased traffic, higher speed links, and the migration to 128 bits IPv6 addresses. IP lookup time is dependent on data structure of lookup table and search scheme. In this paper, we propose a new approach to build a lookup table that satisfies the memory constraint. The design of lookup table is formulated as an optimization problem. The objective is to minimize average depth from the root node for lookup. We assume that the frequencies with which prefixes are accessed are known and the data structure is level compressed trie with branching factor $\kappa$ at the root and binary at all other nodes. Thus, the problem is to determine the branching factor k at the root node such that the average depth is minimized. A heuristic procedure is proposed to solve the problem. Experimental results show that the lookup table based on the proposed heuristic has better average and the worst-case depth for lookup.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4B
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• pp.455-463
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• 2004

In this paper, we deal with a ring-mesh network design problem arising from the deployment of WDM for the optical internet. The ring-mesh network consists of ring topology and full mesh topology for satisfying traffic demand while minimizing the cost of OAOMs and OXCs. The problem seeks to find an optimal clustering of traffic demands in the network such that the total number of node assignments is minimized, while satisfying ring capacity and node cardinality constraints. We formulate the problem as a mixed-integer programming model and prescribe a tabu search heuristic procedure Promising computational results within 3% optimality gap are obtained using the proposed method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.2
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• pp.88-94
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• 2003

In this paper, we propose a hierarchical triangular mesh generation method based on the motion information and a fast rude convergence method. From the variance of Image difference we decide the region that subdivision is required and perform the adequate triangulation method that is possible to yield a successive hierarchical triangulation. For fast node convergence, in initial search, we use the refinement method that separate the backgroung and object region and maintain the mesh connection by using the bilinear interpolation. The simulation result demonstrate that proposed triangulation method have performance in PSNR than the conventional BMA or order mesh based method and refinement is appropriate for the case of the mesh size is small.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.598-607
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• 2005

We propose a new external-memory index data structure, the Suffix B-tree. The Suffix B-tree is a B-tree in which the key is a string like the String B-tree. While the node in the String B-tree is implemented with a Patricia trio, the node in the Suffix B-tree is implemented with an array. So the Suffix B-tree is simpler and easier to be Implemented than the String B-tree. Nevertheless, the branching algorithm of the Suffix B-tree is as efficient as that of the String B-tree. Consequently, the Suffix B-tree takes the same worst-case disk accesses as the String B-tree to solve the string matching problem, which is fundamental and important in the area of string algorithms.