• 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 Information Technology Applications and Management
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• v.16 no.4
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• pp.245-261
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• 2009

Since XML emerged as a standard for data exchange on the web, it has been widely used for applications like e-Commerce, CRM, and BI. However, it is common that most of business data is stored in relational database systems, and it is expected that business data management would still be centered around the relational database systems. As such, the technique of viewing relational data as XML and processing XML queries against it is required. To meet such a need, in the SQL/XML standard, the functions to publish relational data as XML are provided. In this paper, we propose the techniques of providing an XML view of relational data defined by an SQL/XML statement in DTD(Document Type Definition), and of processing XPath queries against the XML view by translating them into SQL/XML statements, and describe the validation of such techniques through implementation and tests.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1327-1335
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• 2011

XML is good at representing data with hierarchical and self-describing structure. There is no inherent semantics with XML. However, semantics of XML has come up with us as XML is used in wide and advanced applications. This paper surveyed semantics in XML data processing environment. XML semantics can be categorized into four groups according to its usage; structural semantics, relational semantics, extended semantics, and semantic web. Relational database is still a good alternative for storing and managing large volume of XML documents. We propose an extended relational semantics in order to exploit it in managing XML documents such as query processing.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.23-30
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• 2008

The basic research of context aware in ubiquitous environment is an internet technique and XML. The XML data of continuous stream type are popular in network application through the internet. And also there are researches related to query processing for streaming XML data. As a basic research to efficiently query, we propose not only a labeled ordered tree model representing the XML but also a mining method to extract frequent structures from streaming XML data. That is, XML data to continuously be input are modeled by a stream tree which is called by XFP_tree and we exactly extract the frequent structures from the XFP_tree of current window to mine recent data. The proposed method can be applied to the basis of the query processing and index method for XML stream data.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.67-83
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• 2008

In order to realize ubiquitous computing, it is essential to efficiently use the resources and the computing power of mobile devices. Among others, memory efficiency, energy efficiency, and processing efficiency are required in executing the softwares embedded in mobile devices. In this paper, query processing over XML data in a mobile device where resources are limited is addressed. In a device with limited amount of memory, the techniques of XML. stream query processing need to be employed to process queries over a large volume of XML data Recently, a technique Galled XFrag was proposed whereby XML data is fragmented with the hole-filler model and streamed in fragments for processing. With XFrag, query processing is possible in the mobile device with limited memory without reconstructing the XML data out of its fragment stream. With the hole-filler model, however, memory efficiency is not high because the additional information on holes and fillers needs to be stored. In this paper, we propose a new technique called XFLab whereby XML data is fragmented with the XML labeling scheme which is for representing the structural relationship in XML data, and streamed in fragments for processing. Through implementation and experiments, XML showed that our XFLab outperformed XFrag both in memory usage and processing time.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.673-682
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• 2009

XML data are widely used for data representation and exchange on the Web and the data type is an continuous stream in ubiquitous environment. Therefore there are some mining researches related to the extracting of frequent structures and the efficient query processing of XML stream data. In this paper, we propose a mining method to extract frequent structures of XML stream data in recent window based on the sliding window. XML stream data are modeled as a tree set, called XFP_tree and we quickly extract the frequent structures over recent XML data in the XFP_tree.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.991-998
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• 2002

With the advent of XML and database languages armed with the object-oriented concept and deductive logic, the problem of efficient query processing for them has become a major issue. We describe a way of processing semi-structured XML data through an implementation of a Deductive and Object-oriented Database (DOODB) language with the explanation of query processing. We have shown how to convert an XML data model to a DOODB data model. We have then presented an efficient query processing method based on Connection Graph Resolution. We also present a knowledge-based query processing method that uses the homomorphism of objects in the database and the associative rule of substitutions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.750-757
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• 2003

Many issues about portability and extension of system converting and exchanging information using XML standard data are being studied currently. This paper proposes design using XML processing layer for mediation between client and server to solve the development cost problem for compatibility and extension of client/server environment. This maintains mediation role for programming development between client and server and increases extension of system and portability of hetero geneous environment. This paper implements and designs XML data processing system for EC using XML DB among hetrogeneous databases. We expect cost-down by maintenance of system using this architecture for electronic commerce.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.1-14
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• 2008

This paper is on query processing in the mobile devices where memory capacity is limited. In case that a query against a large volume of XML data is processed in such a mobile device, techniques of fragmenting the XML data into chunks and of streaming and processing them are required. Such techniques make it possible to process queries without materializing the XML data in its entirety. The previous schemes such as XFrag[4], XFPro[5], XFLab[6] are not scalable with respect to the increase of the size of the XML data because they lack proper memory management capability. After some information on XML fragments necessary for query processing is stored, it is not deleted even after it becomes of no use. As such, when the XML fragments are dynamically generated and infinitely streamed, there could be no guarantee of normal completion of query processing. In this paper, we address scalability of query processing over dynamic XML fragment stream, proposing techniques of deleting information on XML fragments accumulated during query processing in order to extend the previous schemes. The performance experiments through implementation showed that our extended schemes considerably outperformed the previous ones in memory efficiency and scalability with respect to the size of the XML data.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.243-253
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• 2005

Dissemination of XML data on the internet could breach the privacy of data providers unless access to the disseminated XML data is carefully controlled. Recently, the methods using encryption have been proposed for such access control. However, in these methods, the performance of processing queries has not been addressed. A query processor cannot identify the contents of encrypted XML data unless the data are decrypted. This limitation incurs overhead of decrypting the parts of the XML data that would not contribute to the query result. In this paper, we propose the notion of query-aware decryption for efficient processing of queries against encrypted XML data. Query-aware decryption allows us to decrypt only those parts that would contribute to the query result. For this purpose, we disseminate an encrypted XML index along with the encrypted XML data. This index, when decrypted, informs us where the query results are located in the encrypted XML data, thus preventing unnecessary decryption for other parts of the data. Since the size of this index is much smaller than that of the encrypted XML data, the cost of decrypting this index is negligible compared with that for unnecessary decryption of the data itself. The experimental results show that our method improves the performance of query processing by up to 6 times compared with those of existing methods. Finally, we formally prove that dissemination of the encrypted XML index does not compromise security.