• Journal of KIISE:Databases
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• v.32 no.1
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• pp.12-23
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• 2005

In the past decade, advances in speed of commodity CPUs have iu out-paced advances in memory latency Main-memory access is therefore increasingly a performance bottleneck for many computer applications, including database systems. To reduce memory access latency, cache memory incorporated in the memory subsystem. but cache memories can reduce the memory latency only when the requested data is found in the cache. This mainly depends on the memory access pattern of the application. At this point, previous research has shown that B+ trees perform much faster than T-trees because B+ trees are more cache conscious than T-trees, and also proposed 'Cache Sensitive B+trees' (CSB. trees) that are more cache conscious than B+trees. The goal of this paper is to make T-trees be cache conscious as CSB-trees. We propose a new index structure called a 'Cache Sensitive T-trees (CST-trees)'. We implemented CST-trees and compared performance of CST-trees with performance of other index structures.

• Journal of KIISE
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• v.42 no.10
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• pp.1247-1253
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• 2015

An inverted index structure is widely used for efficient string similarity search. One of the main requirements of similarity search is a fast response time; to this end, most techniques use an in-memory index structure. Since the size of an inverted index structure usually very large, however, it is not practical to assume that an index structure will fit into the main memory. To alleviate this problem, we propose a novel technique that reduces the size of an inverted index. In order to reduce the size of an index, the proposed technique rearranges data strings so that the data strings containing the same q-grams can be placed close to one other. Then, the technique encodes those multiple strings into a range. Through an experimental study using real data sets, we show that our technique significantly reduces the size of an inverted index without sacrificing query processing time.

• Journal of KIISE:Databases
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• v.33 no.3
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• pp.271-281
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• 2006

Recently the need for Location-Based Service (LBS) has increased due to the development and widespread use of the mobile devices (e.g., PDAs, cellular phones, labtop computers, GPS, and RFID etc). The core technology of LBS is a moving-objects database that stores and manages the positions of moving objects. To search for information quickly, the database needs to contain an index that supports both real-time position tracking and management of large numbers of updates. As a result, the index requires a structure operating in the main memory for real-time processing and requires a technique to migrate part of the index from the main memory to disk storage (or from disk storage to the main memory) to manage large volumes of data. To satisfy these requirements, this paper suggests a unified index scheme unifying the main memory and the disk as well as migration policies for migrating part of the index from the memory to the disk during a restriction in memory space. Migration policy determines a group of nodes, called the migration subtree, and migrates the group as a unit to reduce disk I/O. This method takes advantage of bulk operations and dynamic clustering. The unified index is created by applying various migration policies. This paper measures and compares the performance of the migration policies using experimental evaluation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1828-1834
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• 2004

With the rapid development of wireless communications and mobile technologies, requirements of various services based on moving objects like location-based services and mobile applications services have been increased. In this paper, we propose an index structure which can improve the performance on trajectory-based query especially, one of the various query types for moving objects in mobile applications. It maintains link table(L-Table) to obtain good efficiency on retrieval and insertion performance of the existing TB(Trajectory Bundle)-tree proposed for trajectory-based query of moving objects. The L-Table contains page number in disk and memory pointers pointing the leaf node with the first and last line segment of moving objects in order to directly access preceding node. In addition, we design to reside a part of whole index in main memory by preserving a fixed size of buffer in case of being restricted by available main memory. Finally, experimental results with various data sets show that the proposed technique is superior to the existing index structures with respect to insertion and trajectory-based query.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.17-28
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• 2008

Recently, main memory access is a performance bottleneck for many computer applications. Cache memory is introduced in order to reduce memory access latency. However, it is possible for cache memory to reduce memory access latency, when desired data are located on cache. EST tree is proposed to solve this problem by improving T tree. However, when doing a range search, EST tree has to search unnecessary nodes. Therefore, this paper proposes $CST^+$ tree which has the merit of CST tree and is possible to do a range search by linking data nodes with linked lists. By experiments, we show that $CST^+$ is $4{\sim}10$ times as fast as CST and $CSB^+$. In addition, rebuilding an index Is an essential step for the database recovery from system failure. In this paper, we propose a fast tree index rebuilding algorithm called MaxPL. MaxPL has no node-split overhead and employs a parallelism for reading the data records and inserting the keys into the index. We show that MaxPL is $2{\sim}11$ times as fast as sequential insert and batch insert.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.13-20
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• 2009

Recently there is growing interest in LBS requiring real-time services and the spatial main memory DBMS for efficient Telematics services. In order to optimize existing disk-based spatial indexes of the spatial main memory DBMS in the main memory, spatial index structures have been proposed, which minimize failures in cache access by reducing the entry size. However, because the reduction of entry size requires compression based on the MBR of the parent node or the removal of redundant MBR, the cost of MBR reconstruction increases in index update and the efficiency of search is lowered in index search. Thus, to reduce the cost of MBR reconstruction, this paper proposed the RSMB (relative-sized MBR)compression technique, which applies the base point of compression differently in case of broad distribution and narrow distribution. In case of broad distribution, compression is made based on the left-bottom point of the extended MBR of the parent node, and in case of narrow distribution, the whole MBR is divided into cells of the same size and compression is made based on the left-bottom point of each cell. In addition, MBR was compressed using a relative coordinate and size to reduce the cost of search in index search. Lastly, we evaluated the performance of the proposed RSMBR compression technique using real data, and proved its superiority.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.210-212
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• 2000

In this paper, we present a comcurrency control scheme over the index structure in main memory databases using multiversion mechanism, and implement it on T-tree. As a well-known idea for comcurrency control, multiversion allows multiple transactions to reat and write different versions of the same data item, each transaction sees a consistent set of versions for all the data items it accesses[1]. Logical versioning and physical versioning techniques are used to keep versions of data item and versions of index node respectively. The main features of this multiversion indexing approach are (1)update operations and rotations on T-tree can take place concurrently, (2)the number of locking and latching requirement is sharply reduced because read-only transactions do not obtain any locks or latches and update transactions obtain latches only when actually performing the update, (3)it reduces storage overhead for tracking version and reclaims storage in time, and (4)it provides complete isolation of read-only transactions from update transactions, so the read-only transactions can get response information without any block.

• International Journal of Contents
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• v.11 no.1
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• pp.69-72
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• 2015

Generally, existing parallel main-memory spatial index structures to avoid the trade-off between query freshness and CPU cost uses light-weight locking techniques. However, still, the lock based methods have some limits such as thrashing which is a well-known problem in lock based methods. In this paper, we propose a distributed index structure for moving objects exploiting the parallelism in multiple machines. The proposed index is a lock free multi-version concurrency technique based on the D-Stream model of Spark Stream. The proposed method exploits the multiversion nature of D-Stream of Spark Streaming.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.794-796
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• 2003

주기억 데이타베이스 시스템은 기존의 디스크 기반 데이타베이스 시스템과 달리 빠른 처리속도와 주기억 장치의 효율적인 사용이 주된 관심 사항이다. 본 논문에서는 주기억 데이타베이스에서 공간 데이터를 위한 효율적인 인덱스구조를 제시한다. 기존에 제시된 주기억 데이타베이스를 위한 인덱스 기법으로는 T-트리, Hash 계열 기법등이 제시되었으나, 이러한 모든 인덱스 기법은 1차원 데이타를 위한 인덱스 기법으로 공간 데이타에는 적용이 불가능하다. 이러한 제약을 극복하기 위해서 본 논문에서는 T-트리에 R-트리 개념을 추가 하였다.

• Journal of KIISE
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• v.43 no.5
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• pp.590-595
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• 2016

In this study, we propose an efficient method for monitoring continuous top-k queries. In contrast to the conventional top-k queries, the presented top-k query considers both spatial and non-spatial attributes. We proposed a novel main-memory based grid access method, called Bit-Vector Grid Index (BVGI). The proposed method quickly identifies whether the moving objects are included in some of the grid cell by encoding a non-spatial attribute value of the moving object to bit-vector. Experimental simulations demonstrate that the proposed method is several times faster than the previous method and uses considerably less memory.