• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07b
• /
• pp.4-6
• /
• 2005

스트림 데이터를 생성하는 응용의 증가로 스트림 데이터 처리에 대한 연구가 활발히 진행되고 있다. 이러한 응용의 예로 센서네트워크, 모니터링, Selective dissemination of information(SDI)등이 있다. 특히 SDI와 같은 웹 환경의 응용은 XML을 기반으로 스트림 데이터 처리에 대한 연구를 진행하고 있다. XML은 웹상의 데이터 교환의 표준으로 웹 응용의 증가로 인해 스트림 데이터 처리 분야에서도 XML을 사용하는 스트림 데이터 처리 시스템에 대한 연구가 많이 진행되고 있는 실정이다. 하지만 XML을 기반으로 하는 기존의 시스템들은 정적인 질의계획을 사용하여 스트림 데이터를 처리하기 때문에 동적으로 변하는 스트림 데이터에 적응력있게 대처할 수 있다. 이와 달리 관계 데이터 모델을 사용하는 스트림 데이터 처리 시스템은 동적인 질의 계획과 질의 처리 연산자의 라우팅(스케쥴링) 기법을 사용하여 적응력있는 질의처리를 지원한다. 본 논문에서는 관계 데이터 모델을 사용하는 시스템의 적응력있는 질의처리 모델을 XML을 기반으로 하는 시스템에 적용하는 기법들에 대하여 설명한다. 그리고 XML을 기반으로 하는 기존의 대표적인 시스템인 YFilter[7]와 본 논문의 제안하는 시스템과의 질의처리 성능을 비교 평가한다.

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

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

• The Journal of Society for e-Business Studies
• /
• v.14 no.4
• /
• pp.75-94
• /
• 2009

Since XML emerged as a standard for data exchange on the web, it has been established as a core component in e-Commerce and efficient query processing over XML data in ubiquitous computing environment has been also receiving much attention. Recently, the techniques were proposed whereby an XML document is fragmented into XML fragments to be streamed and the mobile clients receive the stream while processing queries over it. In processing queries over an XML fragment stream, the average access time significantly depends on the order of fragments in the stream. As such, for query performance, an efficient organization of XML fragment stream is required as well as the indexing for energy-efficient query processing due to the reduction of tuning time. In this paper, a technique of XML fragment stream organization based on query frequencies, fragment size, fragment access frequencies, and an active XML-based indexing scheme are proposed. Through implementation and performance experiments, our techniques were shown to be efficient compared with the conventional XML fragment stream organizations.

• The KIPS Transactions:PartD
• /
• v.16D no.1
• /
• pp.27-42
• /
• 2009

In realizing ubiquitous computing, techniques of efficiently using the limited resource at client such as mobile devices are required. With a mobile device with limited amount of memory, the techniques of XML stream query processing should be employed to process queries over a large volume of XML data. Recently, several techniques were proposed which fragment XML documents into XML fragments and stream them for query processing at client. During query processing, there could be great difference in resource usage (query processing time and memory usage) depending on how the source XML documents are fragmented. As such, an efficient fragmentation technique is needed. In this paper, we propose an XML fragmentation technique whereby resource efficiency in query processing at client could be enhanced. For this, we first present a cost model of query processing over XML fragment stream. Then, we propose an algorithm for resource-efficient XML fragmentation. Through implementation and experiments, we showed that our fragmentation technique outperformed previous techniques both in processing time and memory usage. The contribution of this paper is to have made the techniques of query processing over XML fragment stream more feasible for practical use.

• The KIPS Transactions:PartD
• /
• v.11D no.7 s.96
• /
• pp.1375-1384
• /
• 2004

Streaming data processing is an area of interest with much research under way. There has been increasing attention on the demands for efficient processing of streaming data produced in the application areas such as monitoring and sensor network. We have developed a continuous query processing system for streaming data and evaluated its performance in this paper. XML, the standard for data exchange on the web, is used as the model for the streaming data and the XQuery appended with a time interval is adopted as the query language for expressing con-tinuous queries. In the proposed system, the result is produced through background processing and materialized for reute in subsequent query processing. Through a detailed set of performance experiments, we shoed the effectiveness of the proposed system.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10c
• /
• pp.113-117
• /
• 2006

유비쿼터스 컴퓨팅의 실현을 위해서는 이동 단말기의 자원 및 컴퓨팅 파워의 효율적 사용이 필수적이다. 특히, 이동 단말기에 내장된 소프트웨어의 수행에 있어 메모리 효율성, 에너지 효율성, 그리고 처리 효율성이 요구된다. 본 논문은 자원이 제약되어 있는 이동 단말기에서의 XML 데이터에 대한 질의 처리 기술에 관한 것이다. 메모리 용량이 크지 않은 단말기의 경우 대량의 XML 데이터에 대한 질의 처리를 수행하기 위해서는 XML 스트림 질의 처리 기술이 활용되어야 한다. 최근에 제시된 XFrag 기법은 홀-필러(hole-filler) 모델을 이용하여 XML 데이터를 XML 조각(fragment)으로 분할(fragmentation)하여 스트림으로 전송하고 처리할 수 있는 기법이다. 이는 메모리 효율성이 요구되는 이동 단말기에서 전체 XML 문서를 재구성하지 않고 XML 데이터에 대한 질의 처리를 가능하게 한다. 그러나 홀-필러 모델을 사용할 경우 홀과 필러에 대한 부가적인 정보를 저장해야 하므로 메모리 효율성이 높지 못하다. 본 논문에서는 XML 데이터의 구조 정보를 표현하는 XML 레이블링(labelling) 기법을 이용하여 XML 데이터를 조각으로 분할하여 조각 스트림에 대한 질의 처리를 수행하는 기법을 제시한다. 구현 및 성능 실험 결과 본 논문에서 제시한 기법이 기존의 XFrag 기법보다 메모리 사용량과 처리 시간 양면 모두에서 우수한 것으로 나타났다.

• Journal of KIISE:Databases
• /
• v.35 no.4
• /
• pp.307-318
• /
• 2008

One of the primary issues confronting XML message brokers is the difficulty associated with processing a large set of continuous XPath queries over incoming XML seams. This paper proposes a novel system designed to present an effective solution to this problem. The proposed system transforms multiple XPath queries before their run-time into a new region-based data structure, called an XP-table, by sharing their common constraints. An XP-table is matched with a stream relation (SR) transformed from a target XML stream by a SAX parser. This arrangement is intended to minimize the runtime workload of continuous query processing. Also, system performance is estimated and verified through a variety of experiments, including comparisons with previous approaches such as YFilter and LazyDFA. The proposed system is practically linear- scalable and stable for evaluating a set of XPath queries in a continuous and timely fashion.

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

• The KIPS Transactions:PartD
• /
• v.17D no.5
• /
• pp.353-358
• /
• 2010

Unlike the traditional databases, queries on XML streams are restricted to a real time processing and memory usage. In this paper, a robust labeling scheme is proposed, which quickly identifies structural relationship between XML fragments. The proposed labeling scheme provides an effective query processing by removing many redundant operations and minimizing the number of fragments being processed. In experimental results, the proposed labeling scheme efficiently processes query processing and optimizes memory usage.