• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.134-144
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• 1996

In this paper, we propose a new access method, called the HG-tree, to support indexing and retrieval by image content in large image databases. Image content is represented by a point in a multidimensional feature space. The types of queries considered are the range query and the nearest-neighbor query, both in a multidimensional space. Our goals are twofold: increasing the storage utilization and decreasing the area covered by the directory regions of the index tree. The high storage utilization and the small directory area reduce the number of nodes that have to be touched during the query processing. The first goal is achieved by absorbing splitting if possible, and when splitting is necessary, converting two nodes to three. The second goal is achieved by maintaining the area occupied by the directory region minimally on the directory nodes. We note that there is a trade-off between the two design goals, but the HG-tree is so flexible that it can control the trade-off. We present the design of our access method and associated algorithms. In addition, we report the results of a series of tests, comparing the proposed access method with the buddy-tree, which is one of the most successful point access methods for a multidimensional space. The results show the superiority of our method.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.511-537
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• 2013

Numerous data intensive applications demand the efficient processing of a new type of query, which is called a progressive query (PQ). A PQ consists of a set of unpredictable but inter-related step-queries (SQ) that are specified by its user in a sequence of steps. A conventional DBMS was not designed to efficiently process such PQs. In our earlier work, we introduced a materialized view based approach for efficiently processing PQs, where the focus was on selecting promising views for materialization. The problem of how to efficiently find usable views from the materialized set in order to answer the SQs for a PQ remains open. In this paper, we present a new index technique, called the Dynamic Materialized View Index (DMVI), to rapidly discover usable views for answering a given SQ. The structure of the proposed index is a special ordered tree where the SQ domain tables are used as search keys and some bitmaps are kept at the leaf nodes for refined filtering. A two-level priority rule is adopted to order domain tables in the tree, which facilitates the efficient maintenance of the tree by taking into account the dynamic characteristics of various types of materialized views for PQs. The bitmap encoding methods and the strategies/algorithms to construct, search, and maintain the DMVI are suggested. The extensive experimental results demonstrate that our index technique is quite promising in improving the performance of the materialized view based query processing approach for PQs.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1367-1383
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• 2007

A sensor network consists of a network of sensors that can perform computation and also communicate with each other through wireless communication. Some important characteristics of sensor networks are that the network should be self administered and the power efficiency should be greatly considered due to the fact that it uses battery power. In sensor networks, when large amounts of various stream data is produced and multiple queries need to be processed simultaneously, the power efficiency should be maximized. This work proposes a technique to create an index on multiple monitoring queries so that the multi-query processing performance could be increased and the memory and power could be efficiently used. The proposed SMILE tree modifies and combines the ideas of spatial indexing techniques such as k-d trees and R+-trees. The k-d tree can divide the dimensions at each level, while the R+-tree improves the R-tree by dividing the space into a hierarchical manner and reduces the overlapping areas. By applying the SMILE tree on multiple queries and using it on stream data in sensor networks, the response time for finding an indexed query takes in some cases 50% of the time taken for a linear search to find the query.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.1-18
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• 2008

Because we can usually get many information through analyzing trajectories of moving objects on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks such as FNR-tree and MON-tree. Also, because FNR-tree and MON-tree store the segment unit of moving objects, they can't support the trajectory of whole moving objects. In this paper, we propose an efficient trajectory index structures based on signatures on a spatial network, named SigMO-Tree. For this, we divide moving object data into spatial and temporal attributes, and design an index structure which supports not only range query but trajectory query by preserving the whole trajectory of moving objects. In addition, we divide user queries into trajectory query based on spatio-temporal area and similar-tralectory query, and propose query processing algorithms to support them. The algorithm uses a signature file in order to retrieve candidate trajectories efficiently Finally, we show from our performance analysis that our trajectory index structure outperforms the existing index structures like FNR-Tree and MON-Tree.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1460-1478
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• 2020

This paper proposes a novel anti-collision protocol for large-scale RFID tags identification, named Bi-response Collision Tree Protocol (BCT). In BCT, two group of tags answer the reader's same query in two response-cycles respectively and independently according to the bi-response pattern. BCT improves the RFID tag identification performance significantly by decreasing the query cycles and the bits transmitted by the reader and tags during the identification. Computation and simulation results indicate that BCT improves the RFID tag identification performance effectively, e.g. the tag identification speed is improved more than 13.0%, 16.9%, and 22.9% compared to that of Collision Tree Protocol (CT), M-ary Collision Tree Protocol (MCT), and Dual Prefix Probe Scheme (DPPS) respectively when tags IDs are distributed uniformly.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.598-603
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• 2014

In wireless sensor networks, two methods have been generally used to track continuously moving object: a user query-based method and a periodic report-based method. Although the former method generates more overhead as a result of the user queries, the former one is also an energy-efficient method that does not transfer unnecessary information. For the user query-based method, a virtual tree that consist of sensor nodes is used to perform the user query and the sensor reporting. The tree stores the information of the mobile objects, and the stored information triggers a report b the user query. However, in case of a fast-moving object, the tracking accuracy decreases as a result of the time delay of the end-to-end repeated query. In order to solve this problem, we propose a query-relay method that reduces the time delay for mobile object tracking. In the proposed method, the nodes in the tree relay the query to adjacent nodes according to the movement of mobile object that is tracked. When the query messages are relayed. The end-to-end querying time delay is reduced. and a simulation shows that our method is superior to existing ones in terms of tracking accuracy.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.377-386
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• 2001

In spatial database system, spatial view is supported for efficient access method to spatial database and is managed by materialization and non-materialization technique. In non-materialization technique, repeated execution on the same query makes problems such as the bottle-neck effect of server-side and overloads on a network. In materialization technique, view maintenance technique is very difficult and maintenance cost is too high when the base table has been changed. In this paper, the SVMT (Spatial View Materialization Technique) is proposed by using R-tree re-construction. The SVMT is a technique which constructs a spatial index according to the distribution ratio of objects in spatial view. This ratio is computed by using a SVHR (Spatial View Height in R-tree) and SVOC (Spatial View Object Count). If the ratio is higher than the average, a spatial view is materialized and the R-tree index is re-used. In this case, the root node of this index is exchanged a node which has a MBR (Minimum Boundary Rectangle) value that can contains the whole region of spatial view at a minimum size. Otherwise, a spatial view is materialized and the R-tree is re-constructed. In this technique, the information of spatial view is managed by using a SVIT (Spatial View Information Table) and is stored on the record of this table. The proposed technique increases the speed of response time through fast query processing on a materialized view and eliminates additional costs occurred from repeatable query modification on the same query. With these advantages, it can greatly minimize the network overloads and the bottle-neck effect on the server.

• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.24-34
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• 2015

With the development of the semantic web, a large amount of data being produced nowadays is in RDF format. RDF is represented by a triple. An RDF database consisting of triples requires the high cost of join query processing. Materialized view is known as a scheme to reduce the query processing cost by accessing materialized views without accessing the database. It is physically stored the results or the intermediate results of the query processing in a storage area. In this paper, we propose a materialized view selection scheme by using decision tree to solve such a problem. The decision tree considers the size and maintenance costs of the materialized view as well as the profit of query response times. It is shown through performance evaluation that the proposed scheme increases the number of materialized views in the limited storage space and decreases the update rates of the materialized views.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2294-2304
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• 1999

Our research purpose in this paper is to improve the performance of query processing in GIS(Geographic Information System) by enhancing the I/O performance exploiting parallel I/O and efficient disk access. By packing adjacent spatial data, which are very likely to be referenced concurrently, into one block or continuous disk blocks, the number of disk accesses and the disk access overhead for query processing can be decreased, and this eventually leads to the I/O time decrease. So, in this paper, we proposes EPR(Enhanced Parallel R-tree) indexing method which integrates the parallel I/O method of the previous Parallel R-tree method and a packing-based clustering method. The major characteristics of EPR method are as follows. First, EPR method arranges spatial data in the increasing order of proximity by using Hilbert space filling curve, and builds a packed R-tree by bottom-up manner. Second, with packing-based clustering in which arranged spatial data are clustered into continuous disk blocks, EPR method generates spatial data clusters. Third, EPR method distributes EPR index nodes and spatial data clusters on multiple disks through round-robin striping. Experimental results show that EPR method achieves up to 30% or more gains over PR method in query processing speed. In particular, the larger the size of disk blocks is and the smaller the size of spatial data objects is, the better the performance of query processing by EPR method is.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.382-388
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• 2011

This paper proposes a mechanism that guarantees secured performance against DDoS attack to protect data from free-roaming agent. Also, as it makes up QCRT(query chain relationship tree) structure which is an enhanced chain relation of existing chain relations that improves extension, It also finds malicious elements. The proposed mechanism extends chain relationship of agent as well by checking chain relation structure as a structure according to the route of agent. For it complements existing weakness with single-side chain relation extension, it guarantees secure performance against DDoS and truncation attacks from mobile agent.