• The Journal of the Korea Contents Association
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• v.6 no.4
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• pp.19-28
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• 2006

XML instances for purpose of information exchange are normally stored in the legacy relational database. Therefore, integrations with relational database are required for effective XML applications. To support these requirements, virtual decomposition storage or decomposition storage methods which save separates structures of instances to relational database have researched. However, these storage methods contain different information of schema structure and layers which has caused difficulties to process query during search operation as well as increased overheads due to duplicate savings for separate storages. Therefore, in this research, additional field of 'Eltype' has introduced to previous database schema structure to instance and schema structure, provide consistent level information and propose storage structure to map each field to schema field of relational database. As results, XML instance and structures can be stored together to minimize overheads and required storage-space. Also, synchronized storage layer structure provides easier processing of search query.

• Journal of KIISE:Databases
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• v.35 no.3
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• pp.208-217
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• 2008

Sensors have a function to gather environment-related information operating by small-size battery in sensor networks. The issue related with energy is still an important in spite of the recent advancements in micro-electro-mechanical-system(MEMS) related techology. Generally it is assumed that replacement or rechargement of battery power in sensor is not feasible and a message send operation may spend at least 1000 times battery than a local operation. Thus, there have been several kinds of research efforts to lessen the number of unnecessary messages by maintaining the information of the other neighboring(or all) sensors. In this paper, we propose an index structure based on parent-children relationship to the purpose. Namely, parent node gathers the set of location information and MBA per child. It's named PH and may allow to process the range query with higher accurate and small size information. Through extensive experiments, we show that our index structure has better energy consumption.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4B
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• pp.303-310
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• 2006

In sensor network environments, a sensor node has a limited power because of their resource constraints. Therefore it is important to efficiently use its power in sensor networks. Power consumption of sensor node is closely related to its amount of transmission data. So, we need to reduce the transmission data in order to minimize the power consumption. And sensor networks are inherently unreliable because radio transmission can fail, node can move, and so on. In this paper, we propose the reliable data aggregation protocol in order to these problems. This protocol performs the routing and the query inserting process at the same time to minimize the packet loss caused by network changes. And, this protocol removes the unnecessary routing caused by the periodic routing without query. Additionally, we suggest the countermeasure algorithm against the frequent errors in sensor networks.

• Journal of KIISE:Information Networking
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• v.29 no.3
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• pp.265-275
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• 2002

A default server strategy is a very popular scheme for managing location and state information of mobile hosts in cellular networks. But the communication cost increases if the call requests are frequent and the distant between the default server and the client is long. Still more any connection to a mobile host cannot be established when the default server of the destination mobile host fails. These problems can be solved by replicating default server and by letting nearest replicated default server process the query request which is sent from a client. It is important to allocate replicated default servers efficiently in networks and determine the number of replicated default servers. In this paper, we suggest and evaluate a default server replication strategy to reduce communication costs and to improve service availabilities. Furthermore we propose and evaluate an optimized allocation algorithm and an optimal replication degree for replicating: dofault servers in nn grid networks and binary tree networks.

• Journal of KIISE:Software and Applications
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• v.28 no.10
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• pp.773-784
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• 2001

Since documents on the Web are naturally partitioned into may document database, the efficient information retrieval process requires identifying the document database that are most likely to provide relevant documents to the query and then querying the identified document database. We propose a neural net agent approach to such an efficient information retrieval. First, we present a neural net agent that learns about underlying document database using the relevance feedbacks obtained from many retrieval experiences. For a given query, the neural net agent, which is sufficiently trained on the basis of the BPN learning mechanism, discovers the document database associated with the relevant documents and retrieves those documents effectively. In the experiment, we introduce a neural net agent based information retrieval system and evaluate its performance by comparing experimental results to those of the conventional well-known approaches.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.1-16
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• 2005

When Web-based special retrieval systems for scientific field extremely restrict the expression of user's information request, the process of the information content analysis and that of the information acquisition become inconsistent. Accordingly, this study suggests the re-ranking retrieval model which reflects the content based similarity between user's inquiry terms and index words by grasping the document knowledge structure. In order to accomplish this, the former constructs a thesaurus and similarity relation matrix to provide the subject analysis mechanism and the latter propose the algorithm which establishes a search model such as query expansion in order to analyze the user's demands. Therefore, the algorithm that this study suggests as retrieval utilizing the information structure of a retrieval system can be content-based retrieval mechanism to establish a 2-step search model for the preservation of recall and improvement of accuracy which was a weak point of the previous fuzzy retrieval model.

• Journal of KIISE:Databases
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• v.32 no.2
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• pp.129-141
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• 2005

Although spatio-temporal databases have received considerable attention recently, there has been little work on processing range sum queries on the historical records of moving objects despite their importance. Since to answer range sum queries, the direct access to a huge amount of data incurs prohibitive computation cost, materialization techniques based on existing index structures are recently suggested. A simple but effective solution is to apply the materialization technique to the MVR-tree known as the most efficient structure for window queries with spatio-temporal conditions. However, the MVR-tree has a difficulty in maintaining pre-aggregated results inside its internal nodes due to cyclic paths between nodes. Aggregate structures based on other index structures such as the HR-tree and the 3DR-tree do not provide satisfactory query performance. In this paper, we propose a new indexing technique called the Adaptive Partitioned Aggregate R-Tree (APART) and query processing algorithms to efficiently process range sum queries in many situations. Experimental results show that the performance of the APART is typically above 2 times better than existing aggregate structures in a wide range of scenarios.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.628-638
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• 1999

In this paper, we presents a method of retrieving 24 bpp RGB images based on color-spatial features. For each image, it is subdivided into regions by using similarity of color after converting RGB color space to CIE L*u*v* color space that is perceptually uniform. Our segmentation algorithm constrains the size of region because a small region is discardable and a large region is difficult to extract spatial feature. For each region, averaging color and center of region are extracted to construct color-spatial features. During the image retrieval process, the color and spatial features of query are compared with those of the database images using our similarity measure to determine the set of candidate images to be retrieved. We implement a content-based color image retrieval system using the proposed method. The system is able to retrieve images by user graphic or example image query. Experimental results show that Recall/Precision is 0.80/0.84.

• Journal of KIISE
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• v.43 no.7
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• pp.820-826
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• 2016

There is a growing requirement for big data processing which extracts valuable information from a large amount of data. The Hadoop system employs the MapReduce framework to process big data. However, MapReduce has limitations such as inflexible and slow data processing. To overcome these drawbacks, SQL query processing techniques known as SQL-on-Hadoop were developed. Apache Tajo, one of the SQL-on-Hadoop techniques, was developed by a Korean development group. External merge sort is one of the heavily used algorithms in Tajo for query processing. The performance of external merge sort in Tajo is influenced by two parameters, sort buffer size and fanout. In this paper, we analyzed the performance of external merge sort in Tajo with various sort buffer sizes and fanouts. In addition, we figured out that there are two major causes of differences in the performance of external merge sort: CPU cache misses which increase as the sort buffer size grows; and the number of merge passes determined by fanout.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.281-292
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• 2004

Selectivity estimation for spatial query is very important process used in finding the most efficient execution plan. Many works have been performed to estimate accurate selectivity. Although they deal with some problems such as false-count, multi-count, they can not get such effects in little memory space. Therefore, we propose a new technique called MW Histogram which is able to compress summary data and get reasonable results and has a flexible structure to react dynamic update. Our method is based on two techniques : (a) MinSkew partitioning algorithm which deal with skewed spatial datasets efficiently (b) Wavelet transformation which compression effect is proven. The experimental results showed that the MW Histogram which the buckets and wavelet coefficients ratio is 0.3 is lower relative error than MinSkew Histogram about 5%-20% queries, demonstrates that MW histogram gets a good selectivity in little memory.