• Journal of KIISE:Databases
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• v.33 no.2
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• pp.188-200
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• 2006

Once a continuous query, which is commonly used in sensor networks, is issued, the query is executed many times with a certain interval and the results of those query executions are collected to the base station. Since this comes many communication messages continuously, it is important to reduce communication cost for collecting data to the base station. In sensor networks, in-network processing reduces the number of message transmissions by partially aggregating results of an aggregate query in intermediate nodes, or merging the results in one message, resulting in reduction of communication cost. In this paper, we propose a routing tree for sensor nodes that qualify the given query predicate, called the query specific routing tree(QSRT). The idea of the QSRT is to maximize in-network processing opportunity. A QSRT is created seperately for each query during dissemination of the query. It is constructed in such a way that during the collection of query results partial aggregation and packet merging of intermediate results can be fully utilized. Our experimental results show that our proposed method can reduce message transmissions more than 18% compared to the existing one.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.23-28
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• 2006

In this paper, a power-aware query processing using optimized distributed R-tree in a sensor network is proposed. The proposed technique is a new approach for processing range queries that uses spatial indexing. Range queries are most often encountered under sensor networks for computing aggregation values. The previous work just addressed the importance but didn't provide any efficient technique for processing range queries. A query processing scheme is thus designed for efficiently processing them. Each node in the sensor network has the MBR of the region where its children nodes and the node itself are located. The range query is evaluated over the region which intersects the geographic location of sensors. It ensures the maximum power savings by avoiding the communication of nodes not participating over the evaluation of the query.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.303-317
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• 2002

In this paper, we design and implement E-COIRS enabling users to query with concepts and image features used for further refining the concepts. For example, E-COIRS supports the query "retrieve images containing black home appliance to north of reception set. "The query includes two types of concepts: IS-A and composite. "home appliance"is an IS-A concept, and "reception set" is a composite concept. For evaluating such a query. E-COIRS includes three important components: a visual image indexer, thesauri and a query processor. Each pair of objects in an mage captured by the visual image indexer is converted into a triple. The triple consists of the two object identifiers (oids) and their spatial relationship. All the features of an object is referenced by its old. A composite concept is detected by the triple thesaurus and IS-A concept is recolonized by the fuzzy term thesaurus. The query processor obtains an image set by matching each triple in a user with an inverted file and CS-Tree. To support efficient storage use and fast retrieval on high-dimensional feature vectors, E-COIRS uses Cell-based Signature tree(CS-Tree). E-COIRS is a more advanced content-based image retrieval system than other systems which support only concepts or image features.

• Journal of KIISE:Databases
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• v.30 no.1
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• pp.52-63
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• 2003

Spatiotemporal moving objects are changing their Positions and/or shape over time in real world. As most of the indices of moving object are based on the R-tree. they have defects of the R-tree which are dead space and overlap. Some of the indices amplify the defects of the R-tree. In the paper, to solve the problems, we propose the MPR-tree(Moving Point R-tree) using Projection operation which has more effective search than existing moving point indices on time slice query and spatiotemporal range query. The MPR-tree connects positions of the same moving objects over time by using linked list, so it processes the combined query about trajectory effectively. The usefulness of the Projection operation is confirmed during processing moving object queries and in practical use of space from experimentation to compare MPR-tree with existing indices of moving objects. The proposed MPR-tree would be useful in the LBS, the car management using GPS, and the navigation system.

• Journal of the Korea Society of Computer and Information
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• v.3 no.4
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• pp.1-9
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• 1998

Temporal Databases store all of informations by time varying, so the temporal query processor has to process very large information. Therefore, we propose an efficient method of query processing by using the relevance checking algorithm of input query and view definition. The relevance checking algorithm of query investigates relevance between the input query of user about base relation and the execution tree of view definition stored in system catalog. And related input query with view definition have a process of the query translation to the execution tree of view. So temporal query processor is able to increase performance of query processor by reducing the number of tuple.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.101-113
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• 2006

A path query is used in XML. Several index structures have been studied for processing the path query efficiently. In recent. the index schemes using suffix tree with structure join method were proposed. ViST is the most representative method among such methods. ViST processes the query using suffix tree and uses B+-tree to reduce the search time of the documents. However, it significantly degrades the search performance when processing the path query. The reason is that it regards the element that is not ancestor-descendant relation in the document as a descendent. In this paper, we propose an efficient index structure to solve the problem of ViST. The query processing method suitable to the index structure is also proposed. It is shown through various experiments that the proposed index structure outperforms the existing index structure in terms of the query processing time.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.46-48
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• 2004

Distributed Hash Table(DHT)를 기반으로 하는 structured P2P에서 복잡 질의를 통친 원하는 자료를 찾는 것은 쉽지 않다. 이와 같은 것들 중 하나가 범위 값을 이용하여 원하는 값을 찾는 range query이다. 본 논문에서는 full binary tree의 특징을 이용하여 structured P2P에서 range query를 수행할 수 있는 mapping 함수와, load balance를 지원하기 위한 방법을 제안한다 또한 실험을 통해서 이 방법들이 어느 정도의 성능을 보여주는 지도 살펴본다.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.453-463
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• 2002

With the prevalence of multi-dimensional data such as images, content-based retrieval of data is becoming increasingly important. To handle multi-dimensional data, multi-dimensional index structures such as the R-tree, Rr-tree, TV-tree, and MVP-tree have been proposed. Numerous research results on how to effectively manipulate these structures have been presented during the last decade. Query processing strategies, which is important for reducing the processing time, is one such area of research. In this paper, we propose query processing algorithms for R-tree based structures. The novel aspect of these algorithms is that they make use of the notion of VP filtering, a concept borrowed from the MVP-tree. The filtering notion allows for delaying of computational overhead until absolutely necessary. By so doing, we attain considerable performance benefits while paying insignificant overhead during the construction of the index structure. We implemented our algorithms and carried out experiments to demonstrate the capability and usefulness of our method. Both for range query and incremental query, for all dimensional index trees, the response time using VP filtering was always shorter than without VP filtering. We quantitatively showed that VP filtering is closely related with the response time of the query.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9B
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• pp.1092-1097
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• 2011

An anti-collision protocol which tries to minimize the collision probability and identification time is the most important factor in all identification technologies. This paper focuses on methods to improve the efficiency of tag's process in identification systems. Our scheme, Binary Slotted Query Tree (BSQT) algorithm, is a memoryless protocol that identifies an object's ID more efficiently by removing the unnecessary prefixes of the traditional Query Tree (QT) algorithm. With enhanced QT algorithm, the reader will broadcast 1 bit and wait the response from the tags but the difference in this scheme is the reader will listen in 2 slots (slot 1 is for 0 bit Tags and slot 2 is for 1 bit Tags). Base on the responses the reader will decide next broadcasted bit. This will help for the reader to remove some unnecessary broadcasted bits which no tags will response. Numerical and simulation results show that the proposed scheme decreases the tag identification time by reducing the overall number of request.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.121-126
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• 2010

This paper proposes an efficient index scheduling technique for kNN query processing in multiple wireless broadcast channel environment. Previous works have to wait for the next cycle if the required child nodes of the same parent node are allocated in the same time slot on multiple channel. Our proposed method computes the access frequencies of each node of R tree at the server before the generation of the R-tree index broadcast schedule. If they have high frequencies, we allocate them serially on the single channel. If they have low frequencies, we allocate them in parallel on the multiple channels. As a result, we can reduce the index node access conflicts and the long broadcast cycle. The performance evaluation shows that our scheme gives the better performance than the existing schemes.