• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3100-3116
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• 2016

With the rapid development of urban traffic system and fast increasing of vehicle numbers, the traditional centralized ways to generate the source-destination shortest path in terms of travel time(the optimal path) encounter several problems, such as high server pressure, low query efficiency, roads state without in-time updating. With the widespread use of smart cameras in the urban traffic and surveillance system, this paper maps the optimal path finding problem in the dynamic road network to the shortest routing problem in the smart camera networks. The proposed distributed optimal path generation algorithm employs the delay routing and caching mechanism. Real-time route update is also presented to adapt to the dynamic road network. The test result shows that this algorithm has advantages in both query time and query packet numbers.

• KIISE Transactions on Computing Practices
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• v.23 no.10
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• pp.605-610
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• 2017

In distributed environments, dynamic partitioning is needed to resolve the load on a particular server or the load caused by communication among servers. In heterogeneous environments, existing dynamic partitioning schemes can distribute the same load to a server with a low physical performance, which results in a delayed query response time. In this paper, we propose a dynamic partitioning scheme for large RDF data in heterogeneous environments. The proposed scheme calculates the query loads with its frequency and the number of vertices used in the query for load balancing. In addition, we calculate the server loads by considering the physical performance of the servers to allocate less of a load to the servers with a smaller physical performance in a heterogeneous environment. We perform dynamic partitioning to minimize the number of edge-cuts to reduce the traffic among servers. To show the superiority of the proposed scheme, we compare it with an existing dynamic partitioning scheme through a performance evaluation.

• 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.

• International Journal of Contents
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• v.6 no.1
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• pp.47-52
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• 2010

Skyline queries are an important new search capability for multi-dimensional databases. Most of the previous works have focused on processing skyline queries over static data set. However, most of the real applications deal with the dynamic data set. Since dynamic data set constantly changes as time passes, the continuous skyline computation over dynamic data set becomes ever more complicated. In this paper, we propose a multiple layer grids method for continuous skyline computation (MLGCS) that maintains multiple layer grids to manage the dynamic data set. The proposed method divides the work space into multiple layer grids and creates the skyline influence region in the grid of each layer. In the continuous environment, the continuous skyline queries are only handled when the updating data points are in the skyline influence region of each layer grid. Experiments based on various data distributions show that our proposed method outperforms the existing methods.

• Journal of KIISE:Information Networking
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• v.31 no.6
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• pp.673-684
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• 2004

As the wireless mobile communication is being widespread, mobile technologies will have important roles in the communication with the explosive growth of demanding for wireless portable devices. Among the mobile technologies, a great deal of interest has been taken in mobile ad hoc network (MANET), which is a collection of wireless mobile nodes forming a temporary network without the aid of stationary infrastructure in recent. Furthermore, considering characteristic of ad hoc networks, the design of efficient routing protocols is an important issue. In recent years, on-demand protocols among routing protocols have noticed because of the low routing overhead. However, on-demand protocols suffer from production of the enormous query Packets by broadcasting in order to setup routes, that is, a flooding scheme. The flooding scheme is very costly and results in serious problem, which we refer as the broadcast storm problem. In this paper, we propose a Dynamic Adaptation Query flooding Using Neighbor Topology (NT-DAQ) scheme, in order to resolve the broadcast storm Problem. When a route discovery is in progress, each mobile node decides on the basis of neighbor topology information whether discovery process participates or not. Therefore, our proposed scheme enables to improve network performance in which minimize the number of query rackets. We evaluate the efficiency of our proposed scheme through simulation.

• Journal of KIISE:Databases
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• v.33 no.3
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• pp.327-341
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• 2006

As we are getting to deal with more applications that generate streaming data such as sensor network, monitoring, and SDI (selective dissemination of information), active research is being conducted to support efficient processing of queries over streaming data. The applications on the Web environment like SDI, among others, require query processing over streaming XML data, and its investigation is very important because XML has been established as the standard for data exchange on the Web. One of the major problems with the previous systems that support query processing over streaming XML data is that they cannot deal adaptively with dynamically changing stream because they rely on static query plans. On the other hand, the stream query processing systems based on relational data model have achieved adaptiveness in query processing due to query operator routing. In this paper, we propose a system of adaptive query processing over streaming XML data in which the model of adaptive query processing over streaming relational data is applied. We compare our system with YFiiter, one of the representative systems that provide XML stream query processing capability, to show efficiency of our system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2158-2164
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• 2015

In u-GIS environments, various load shedding techniques have been researched in order to balance loads caused by input spatial data streams. However, typical load shedding methods on aspatial data lack regard for characteristics of spatial data, also previous load shedding approaches on spatial, which still lack regard for spatial data density or dynamic input data stream, give rise to troubles on spatial query processing performance and accuracy. Therefore, dynamic load shedding scheme over spatial data stream is proposed through stored spatial data deviation and load ratio of input data stream in order to improve spatial continuous query accuracy and performance in u-GIS environment. In proposed scheme, input data which are a big probability related to spatial continuous query may be a strong chance to be dropped relatively.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.408-419
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• 2003

Data warehouses are usually dedicated to the processing of quires issued by decision support system(DSS). The response time of DSS queries is typically several orders of magnitude higher than the one of OLTP queries. Since DSS queries are often submitted interactively, techniques for reducing their response time are important. The caching of query results is one such technique particularly well suited to the DSS environment. In this paper, we present a cache manager for such an environment. Specifically, we define a canonical form of query. The cache manager looks up a query based on the exact query match or using a suggested query split process if the query is found is non-canonical form or in canonical form, respectively. It dynamically maintains the cache content by employing a profit function which reflects in an integrated manner the query execution cost, the size of query result, the reference rate, the maintenance cost of each result due to updates of their base tables, and the frequency of such updates. We performed the experimental evaluation and it positively shows the performance benefit of our cache manager.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1756-1776
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• 2012

Wireless sensor networks (WSNs) are likely to be more prevalent as their cost-effectiveness improves. The spectrum of applications for WSNs spans multiple domains. In environmental sciences, in particular, they are on the way to become an essential technology for monitoring the natural environment and the dynamic behavior of transient physical phenomena over space. Existing sensor network query processors (SNQPs) have also demonstrated that in-network processing is an effective and efficient means of interaction with WSNs for performing queries over live data. Inspired by these findings, this paper investigates the question as to whether spatio-temporal and historical analysis can be carried over WSNs using distributed query-processing techniques. The emphasis of this work is on the spatial, temporal and historical aspects of sensed data, which are not adequately addressed in existing SNQPs. This paper surveys the novel approaches of storing the data and execution of spatio-temporal and historical queries. We introduce the challenges and opportunities of research in the field of in-network storage and in-network spatio-temporal query processing as well as illustrate the current status of research in this field. We also present new areas where the spatio-temporal and historical query processing can be of significant importance.