• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.358-364
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• 2007

This paper suggests MPLS restoration method that use an aggregation tree. For the restoration of the MPLS network, this paper presents a scheme that reconstruct multiple path through aggregation tree that grow from many node to a target node. Contrary to a multicast tree where a message that send at one node is passed to a group of node, an aggregation tree is a tree that data is passed from many node to one destination node. Through an experiment we confirmed that the restoration scheme that uses aggregation tree shows taster speed comparing with the existing other restoration scheme.

• 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 KIISE:Databases
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• v.33 no.5
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• pp.463-475
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• 2006

In applications such as a traffic management system, analysis using a spatial hierarchy of a spatial data warehouse and a simple aggregation is required. Over the past few years, several studies have been made on solution using a spatial index. Many studies have focused on using extended R-tree. But, because it just provides either the current aggregation or the total aggregation, decision support of traffic policy required historical analysis can not be provided. This paper proposes hybrid index based on extended aR-tree for the spatio-temporal aggregation. The proposed method supports a spatial hierarchy and the current aggregation by the R-tree. The sorted hash table using the time structure of the extended aR-tree provides a temporal hierarchy and a historical aggregation. Therefore, the proposed method supports an efficient decision support with spatio-temporal analysis and is Possible currently traffic analysis and determination of a traffic policy with historical analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1057-1059
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• 2016

A construction method of energy-efficient data aggregation tree is proposed by considering a tradeoff between acquisition time and energy consumption in wireless sensor networks. This proposed method constructs the data aggregation tree to minimize the link cost between the connected nodes for reducing energy consumption, while minimizing the maximum distance between sensor nodes and a sink node for rapid information gathering. Simulation results show that the proposed aggregation tree can be generated with low complexity and achieves high energy efficiency compared to conventional methods.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.429-440
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• 2002

Temporal databases manage time-evolving data. They provide built-in supports for efficient recording and querying of temporal data. The temporal aggregate in temporal databases is an extension of the conventional aggregate to include time concept on the domain and range of aggregation. This paper focuses on multidimensional temporal aggregation. In a multidimensional temporal aggregate, we use one or more general attributes as well as a time attribute on the range of aggregation, thus it is a useful operation for historical data warehouse, Call Data Records(CDR), etc. In this paper, we propose a structure for multidimensional temporal aggregation, called PTA-tree, and an aggregate processing method based on the PTA-tree. Through analyses and performance experiments, we also compare the PTA-tree with the simple extension of SB-tree that was proposed for temporal aggregation.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.212-213
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• 2015

Data aggregation is a fundamental problem in wireless sensor networks that has attracted great attention in recent years. On constructing a robust algorithm for minimizing data aggregation delay in wireless sensor networks, we consider limited transmission range sensors and approximate the minimum-delay data aggregation tree which can only be built in networks of unlimited transmission range sensors. The paper proposes an adaptive method that can be applied to maintain the network structure in case of a sensor node fails. The data aggregation tree built by the proposed scheme is therefore self-healing and robust. Intensive simulations are carried out and the results show that the scheme could adapt well to network topology changes compared with other approaches.

• Journal of KIISE:Databases
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• v.35 no.3
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• pp.218-230
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• 2008

The temporal aggregate in temporal databases is an extension of the conventional aggregate to include the time on the range condition of aggregation. It is a useful operation for Historical Data Warehouses, Call Data Records, and so on. In this paper, we propose a structure for the temporal aggregation with multiple selection predicates, called the ITA-tree, and an aggregate processing method based on the structure. In the ITA-tree, we transform the time interval of a record into a single value, called the T-value. Then, we index records according to their T-values like a $B^+$-tree style. For possible hot-spot situations, we also propose an improvement of the ITA-tree, called the eITA-tree. Through analyses and experiments, we evaluate the performance of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.597-618
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• 2019

Categorical range aggregation, which is conceptually equivalent to running a range aggregation query separately on multiple datasets, returns the query result on each dataset. The challenge is when the number of dataset is as large as hundreds or thousands, it takes a lot of computation time and I/O. In previous work, only a single dimension of the range restriction has been solved, and in practice, more applications are being used to calculate multiple range restriction statistics. We proposed MCRI-Tree, an index structure designed to solve multi-dimensional categorical range aggregation queries, which can utilize main memory to maximize the efficiency of CRA queries. Specifically, the MCRI-Tree answers any query in $O(nk^{n-1})$ I/Os (where n is the number of dimensions, and k denotes the maximum number of pages covered in one dimension among all the n dimensions during a query). The practical efficiency of our technique is demonstrated with extensive experiments.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.175-177
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• 2020

In multi-channel wireless sensor networks, optimizing data aggregation delay without any channels and timeslots conflicts has been concerned these days. The aggregation delay can be reduced by using different aggregation tree construction methods or scheduling in different methods in bottom-up or top-down manners. In this paper, we propose a new way of constructing aggregation tree purposing to decrease the total aggregation delay. The result shows that our proposed scheme can improve up to 64% comparing with state-of-the-art schemes.

• The Journal of the Korea Contents Association
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• v.8 no.7
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• pp.35-42
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• 2008

The proposed scheme in this paper can search multi-links efficiently using the depth priority method based on hop count instead of searching the all links. To do this, we proposed a modified line segment scheme using two line segment method. The scheme represents two points which consist of delay-bandwidth pair to reduce topology information and provide a flexibility to the multiple-links aggregation. And we apply it to current spanning tree topology aggregation. To evaluate performance of the proposed scheme, we compare/analyze the current method with the proposed scheme with respect to call success rate, access time and crankback rate. Simulation result analysis showed the proposed spanning tree topology aggregation scheme presents the better performance than existing scheme.