• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.67-76
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• 2018

This paper addresses the problem of efficient processing of region monitoring queries. The centralized methods used for existing region monitoring query processing assumes that the mobile object periodically sends location-updates to the server and the server continues to update the query results. However, a large amount of location updates seriously degrade the system performance. Recently, some distributed methods have been proposed for region monitoring query processing. In the distributed methods, the server allocates to all objects i) a resident domain that is a subspace of the workspace, and ii) a number of nearby query regions. All moving objects send location updates to the server only when they leave the resident domain or cross the boundary of the query region. In order to allocate the resident domain to the moving object along with the nearby query region, we use a query index structure that is constructed by splitting the workspace recursively into equal halves. However, However, the above index structure causes unnecessary division, resulting in deterioration of system performance. In this paper, we propose an adaptive split method to reduce unnecessary splitting. The workspace splitting is dynamically allocated i) considering the spatial relationship between the query region and the resultant subspace, and ii) the distribution of the query region. We proposed an enhanced QR-tree with a new splitting method. Through a set of simulations, we verify the efficiency of the proposed split methods.

• Journal of KIISE
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• v.42 no.1
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• pp.97-106
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• 2015

Recently, research on database encryption for data protection and query result authentication methods has been performed more actively in the database outsourcing environment. Existing database encryption schemes are vulnerable to order matching and counting attack of intruders who have background knowledge of the original database domain. Existing query result integrity auditing methods suffer from the transmission overhead of verification object. To resolve these problems, we propose a group-order preserving encryption index and a query result authentication method based on the encryption index. Our group-order preserving encryption index groups the original data for data encryption and support query processing without data decryption. We generate group ids by using the Hilbert-curve so that we can protect the group information while processing a query. Finally, our periodic function based data grouping and query result authentication scheme can reduce the data size of the query result verification. Through performance evaluation, we show that our method achieves better performance than an existing bucket-based verification scheme, it is 1.6 times faster in terms of query processing time and produces verification data that is 20 times smaller.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.165-175
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• 2016

A data allocation technique is essential to improve the performance of data broadcast systems. This paper explores the issues for allocating data items on broadcast channels to process multiple-data queries in the environment where query profiles and query request rates are given, and proposes a new data allocation scheme named QBDA. The proposed scheme allows the query with higher request rate to have higher priority to schedule its data items and introduces the concept of marking to reduce data conflicts. Simulation is performed to evaluate the performance of QBDA. The simulation results show that the proposed scheme outperforms other schemes in terms of the average response time since it can process queries with high request rate fast and show a very desirable characteristics in the aspects of query data adjacency and data conflict probability.

• 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:Computing Practices and Letters
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• v.14 no.7
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• pp.680-693
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• 2008

Recent studies on XML filtering assume that all data sources follow a single global schema defined in a filtering system. However, beyond this simple assumption, a filtering system can provide a service that allows data publishers to have their own schema; hence, the data sources will become heterogeneous. The number of data sources is expected to be large in a filtering system and the data sources are frequently published, updated, and disappeared, that is, dynamic. In this paper, we introduce implementing a simple and efficient XPath query translation method for such a dynamic environment. The method is especially targeted for a query which is composed based only on users' knowledge and experience without a graphical guidance of the global schema. When a user queries a large number of heterogeneous data, there is a high possibility that the query is not consistent with the same local schema assumed by the user. Our query translation method also supports a function for this problem. Some experimental results for query translation performance have shown that our method has reasonable performance, and is more practical than the existing method.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.7
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• pp.809-813
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• 2010

Many studies on reverse skyline query processing have been done for company oriented services. The existing methods about reverse skyline are reverse skyline based on dynamic skyline. There is no reverse skyline query processing algorithm based on metric spaces for location-based services. In this paper we propose a reverse skyline query processing scheme that applies for a general skyline and considers distance spaces. The proposed method processes reverse skyline queries in the metric spaces using the existing spatial indexing scheme and considers both Monochromatic and Bichromatic environments. In order to show the superiority of the proposed scheme, we compare it with the basic skyline query processing scheme through performance evaluation. As a result, the proposed method excellent performance was about 5000 times more than conventional method.

• Journal of KIISE
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• v.42 no.4
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• pp.522-529
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• 2015

Ever since the R-tree was proposed to index multi-dimensional data, many efforts have been made to improve its query performances. One common trend to improve query performance is to parallelize query processing with the use of multi-core architectures. To this end, a GPU-base R-tree has been recently proposed. However, even though a GPU-based R-tree can exhibit an improvement in query performance, it is limited in its ability to handle large volumes of data because GPUs have limited physical memory. To address this problem, we propose MGR-tree (Multi-GPU R-tree), which can manage large volumes of data by dividing nodes into multiple GPUs. Our experiments show that MGR-tree is up to 9.1 times faster than a sequential search on a GPU and up to 1.6 times faster than a conventional GPU-based R-tree.

• Journal of KIISE:Information Networking
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• v.33 no.6
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• pp.420-427
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• 2006

An RFID system is an important technology that could replace the traditional bar code system changing the paradigm of manufacturing, distribution, and service industry. An RFID reader can recognize several hundred tags in one second. Tag identification is done by tags' random transmission of their IDs in a frame which is assigned by the reader at each round. To minimize tag identification time, optimal frame size should be selected according to the number of tags. This paper presents new query optimization methods in RFID systems. Query optimization consists of tag number estimation problem and frame length determination problem. We propose a simple yet efficient tag estimation method and calculate optimal frame lengths that minimize overall query time. We conducted rigorous performance studies. Performance results show that the new tag number estimation technique is more accurate than previous methods. We also observe that a simple greedy method is as efficient as the optimal method in minimizing the query time.

• Journal of KIISE
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• v.42 no.9
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• pp.1109-1116
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• 2015

In this paper, we propose a query processing approach that uses the Spark functional programming and distributed memory system to solve the computational overhead of SPARQL. In the semantic web, RDF ontology data is produced at large scale, and the main challenge for the semantic web is to query and manipulate such a large ontology with a high throughput. The most existing studies on SPARQL have focused on deploying the Hadoop MapReduce framework, and although approaches based on Hadoop MapReduce have shown promising results, they achieve a low level of throughput due to the underlying distributed file processes. Therefore, in order to speed up the query processes, we suggest query- processing methods that are based on memory caching in distributed memory system. Our approach is also integrated with a clause unification method for propagating between the clauses that exploits Spark join, map and filter methods along with caching. In our experiments, we have achieved a high level of performance relative to other approaches. In particular, our performance was nearly similar to that of Sempala, which has been considered to be the fastest query processing system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.723-736
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• 2014

This paper proposes a matching engine for a query-by-singing/humming (QbSH) system with polyphonic music files like MP3 files. The pitch sequences extracted from polyphonic recordings may be distorted. So we use chroma-scale representation, pre-processing, compensation, and asymmetric dynamic time warping to reduce the influence of the distortions. From the experiment with 28 hour music DB, the performance of our QbSH system based on polyphonic database is very promising in comparison with the published QbSH system based on monophonic database. It shows 0.725 in MRR(Mean Reciprocal Rank). Our matching engine can be used for the QbSH system based on MIDI DB also and that performance was verified by MIREX 2011.