• International Journal of Contents
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• v.3 no.1
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• pp.19-23
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• 2007

Recently, several main-memory index structures have been proposed to reduce the impact of secondary cache misses. In mainmemory storage systems, secondary cache misses have a substantial effect on the performance of index structures. However, recent studies still stiffer from secondary cache misses when visiting each level of index tree. In this paper, we propose a new index structure that minimizes the total amount of cache miss latency. The proposed index structure prefetched grandchildren of a current node. The basic structure of the proposed index structure is based on that of the CSB+-Tree, which uses the concept of a node group to increase fan-out. However, the insert algorithm of the proposed index structure significantly reduces the cost of a split. The superiority of our algorithm is shown through performance evaluation.

• International Journal of Contents
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• v.3 no.3
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• pp.1-5
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• 2007

The main memory DBMS (MMDBMS) efficiently supports various database applications that require high performance since it employs main memory rather than disk as a primary storage. An index manager is an essential sub-component of a DBMS used to speed up the retrieval of objects from a large volume of a database in response to a certain search condition. Previous research efforts on indexing proposed various index structures. However, they hardly dealt with the practical issues occurred in implementing an index manager on a target DBMS. In this paper, we touch these issues and present our experiences in developing the index manager. The main issues are (1) compact representation of an index entry, (2) support of variable-length keys. (3) support of multiple-attribute keys, and (4) support of duplicated keys.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.673-676
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• 2004

To manage and query moving objects efficiently in MMDBMS, a memory index structure should be used. The most popular index structure for storing trajectories of moving objects is 3DR-tree. The 3DR-tree also can be used for MMDBMS. However, the volume of data can exceed the capacity of physical memory since moving objects report their locations continuously. To accommodate new location reports, old trajectories should be migrated to disk or purged from memory. This paper focuses on migration policies of a main memory index structure. Migration policies consist of two steps: (i) node selection, (ii) node placement. The first step (node selection) selects nodes that should be migrated to disk. The criteria of selection are the performance of insertion or query. The second step (node placement) determines the order of nodes written to disk. This step can be thought as dynamic declustering policies.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.11-22
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• 2004

As random access memory chip gets cheaper, it becomes affordable to realize main memory-based database systems. Consequently, reducing cache misses emerges as the most important issue in current main memory databases, in which CPU speeds have been increasing at 60% per year, compared to the memory speeds at 10% per you. In this paper, we design and implement a main-memory database system for real-time mobile GIS. Our system is composed of 5 modules： the interface manager provides the interface for PDA users； the memory data manager controls spatial and non-spatial data in main-memory using virtual memory techniques； the query manager processes spatial and non-spatial query : the index manager manages the MR-tree index for spatial data and the T-tree index for non-spatial index : the GIS server interface provides the interface with disk-based GIS. The MR-tree proposed propagates node splits upward only if one of the internal nodes on the insertion path has empty space. Thus, the internal nodes of the MR-tree are almost 100% full. Our experimental study shows that the two-dimensional MR-tree performs search up to 2.4 times faster than the ordinary R-tree. To use virtual memory techniques, the memory data manager uses page tables for spatial data, non- spatial data, T-tree and MR-tree. And, it uses indirect addressing techniques for fast reloading from disk.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.1867-1879
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• 1997

DREAM-S is a distributed main-memory database system for the real-time processing of shared operational datra in ATM switching systems. DREAM-S has a client-server architecture in which only the server has the diskstorage, and provides the T-Tree index structure for efficient accesses to the data. We propose a recovery technique for the T-Tree index structre in DREAM-S. Although main-memory database system offer efficient access performance, the database int he main-memory may be broken when system failure such as database transaction failure or power failure occurs. Therfore, a recovery technique that recovers the database (including index structures) is essential for fault tolerant ATM switching systems. Proposed recovery technique relieves the bottleneck of the server processors disk operations by maintaining the T-Tree index structure only in the main-memory. In addition, fast recovery is guaranteed even in large number of client systems since the T-Tree index structure(s) in each system can be recovered cncurrently.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.53-73
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• 2006

Recently, the need for Location-Based Services (LBS) has increased due to the development of mobile devices, such as PDAs, cellular phones and GPS. As a moving object database that stores and manages the positions of moving objects is the core technology of LBS, the scheme for maintaining the main memory DBMS to the server is necessary to store and process frequent reported positions of moving objects efficiently. However, previous works on a moving object database have studied mostly a disk based moving object index that is not guaranteed to work efficiently in the main memory DBMS because these indexes did not consider characteristics of the main memory. It is necessary to study the main memory index scheme for a moving object database. In this paper, we propose the main memory index scheme based on the R-tree for storing and processing positions of moving objects efficiently in the main memory DBMS. The proposed index scheme, which uses a growing node structure, prevents the splitting cost from increasing by delaying the node splitting when a node overflows. The proposed scheme also improves the search performance by using a MergeAndSplit policy for reducing overlaps between nodes and a LargeDomainNodeSplit policy for reducing a ratio of a domain size occupied by node's MBRs. Our experiments show that the proposed index scheme outperforms the existing index scheme on the maximum 30% for range queries.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.543-552
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• 2005

As random access memory chip gets cheaper, it becomes affordable to realize main memory-based database systems. The disk-based spatial indexing techniques, however, cannot direct apply to main memory databases, because the main purpose of disk-based techniques is to reduce the number of disk accesses. In main memory-based indexing techniques, the node access time is much faster than that in disk-based indexing techniques, because all index nodes reside in a main memory. Unlike disk-based index techniques, main memory-based spatial indexing techniques must reduce key comparing time as well as node access time. In this paper, we propose an efficient spatial index structure for main memory-based databases, called Tmr-tree. Tmr-tree integrates the characteristics of R-tree and T-tree. Therefore, Nodes of Tmr-tree consist of several entries for data objects, main memory pointers to left and right child, and three additional fields. First is a MBR of a self node, which tightly encloses all data MBRs (Minimum Bounding Rectangles) in a current node, and second and third are MBRs of left and right sub-tree, respectively. Because Tmr-tree needs not to visit all leaf nodes, in terms of search time, proposed Tmr-tree outperforms R-tree in our experiments. As node size is increased, search time is drastically decreased followed by a gradual increase. However, in terms of insertion time, the performance of Tmr-tree was slightly lower than R-tree.

• The Journal of Information Technology and Database
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• v.8 no.2
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• pp.103-114
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• 2001

In this paper, we propose an efficient index mechanism for real-time main memory database systems. Existing main memory index structures based on the tree can effectively support range searches. However, it doesn't guarantee the real-time characteristic because difference between the access time of a node and an average access time can be high. The index structures based on the hash have always a regular random access time on the simple searches and that speed is very fast. However they do not support range searches. To solve such problems, we propose a new index mechanism called Hyper Tree-Hash (Hyper-TH) that combines ECBH (Extendible Chained Bucket Hashing) and T＊-tree. ECBH can be dynamically extended and has a very fast access time. T＊-tree effectively supports the range searches. We show through our experiments that the proposed mechanism outperforms existing other index structures.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.675-683
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• 2004

In main-memory resident index structures, secondary cache misses considerably have an effect on the performance of index structures. Recently, several main-memory resident index structures that consider cache have been proposed to reduce the impact of secondary cache misses. However they still suffer from full secondary cache misses whenever visiting each level of a index tree. In this paper, we propose a new index structure that eliminates cache misses even when visiting each level of index tree. The proposed index structure prefetches the grandchildren of a current node. The basic structure of the proposed index structure is from CSB+-tree that uses the concepts of the node group to increase fan-out. However the insert algorithm of the proposed index structure reduces the cost of a split significantly. Also, we show the superiority of our algorithm through various performance evaluation.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.499-501
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• 2003

As semiconductor memory becomes cheaper, the memory capacity of computer system is increasing. Therefore computer system has sufficient memory for a plentiful spatial data. With emerging spatial application required high performance, this paper presents a GIS database system in main memory. Memory residence can provide both functionality and performance for a database management system. This paper describes design of DBMS for storing, querying, managing and analyzing for spatial and non-spatial data in main-memory. This memory resident GIS DBMS supports SQL for spatial query, spatial data model, spatial index and interface for GIS tool or applications.