• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.101-104
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• 2007

Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.396-417
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• 2018

GR-tree and query aggregation techniques have been proposed for spatial query processing in conventional spatial query processing for wireless sensor networks. Although these spatial query processing techniques consider spatial query optimization, time query optimization is not taken into consideration. The index reorganization cost and communication cost for the parent sensor nodes increase the energy consumption that is required to ensure the most efficient operation in the wireless sensor node. This paper proposes itinerary-based R-tree (IR-tree) for more efficient spatial-temporal query processing in wireless sensor networks. This paper analyzes the performance of previous studies and IR-tree, which are the conventional spatial query processing techniques, with regard to the accuracy, energy consumption, and query processing time of the query results using the wireless sensor data with Uniform, Gauss, and Skew distributions. This paper proves the superiority of the proposed IR-tree-based space-time indexing.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.541-546
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• 2007

Traditional query processing method is not efficient for continuous queries with large continuous stream data. This paper proposes a data-driven query processing method for stream data. The structure of query plan and query execution method are presented. With the proposed method, multiple query processing and sharing among queries can be achieved. Also query execution time can be reduced by storing partial results of query execution. This paper showed an example of query processing with XML data and XQuery query.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.518-532
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• 2017

Due to the rapid growth of the amount of data, research on bigdata processing has been highlighted. For bigdata processing, CUBRID Shard is able to support query processing in parallel way by dividing the database into a number of CUBRID servers. However, CUBRID Shard can answer a user's query only when the query is required to gain accesses to a single CUBRID server, instead of multiple ones. To solve the problem, in this paper we propose a CUBRID based distributed parallel query processing system that can answer a user's query in parallel and distributed manner. Finally, through the performance evaluation, we show that our proposed system provides 2-3 times better performance on query processing time than the existing CUBRID Shard.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1182-1188
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• 2014

Recently, the research on database outsourcing has been actively done with the popularity of cloud computing. However, because users' data may contain sensitive personal information, such as health, financial and location information, the data encryption methods have attracted much interest. Existing data encryption schemes process a query without decrypting the encrypted databases in order to support user privacy protection. On the other hand, to efficiently handle the large amount of data in cloud computing, it is necessary to study the distributed index structure. However, existing index structure and query processing algorithms have a limitation that they only consider single-column query processing. In this paper, we propose a grid-based multi column indexing scheme and an encrypted query processing algorithm. In order to support multi-column query processing, the multi-dimensional index keys are generated by using a space decomposition method, i.e. grid index. To support encrypted query processing over encrypted data, we adopt the Hilbert curve when generating a index key. Finally, we prove that the proposed scheme is more efficient than existing scheme for processing the exact and range query.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.64-72
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• 2021

XML message brokers have a lot of importance because XML has become a practical standard for data exchange in many applications. Message brokers covered in this document store many users. This paper is a study of the processing of twig pattern queries in XML documents using branching node streams in XML message broker structures. This work is about query processing in XML documents, especially for query processing with XML twig patterns in the XML message broker structure and proposed a method to reduce query processing time when parsing documents with XML twig patterns by processing information. In this paper, the twig pattern query processing method of documents using the branching node stream removes the twigging value of the branch node that does not include the labeling value of the branch node stream when it receives a twig query from the client. In this paper, the leaf node discovery time can be reduced by reducing the navigation time of nodes in XML documents that are matched to leaf nodes in twig queries for client twig queries. Overall, the overall processing time to respond to queries is reduced, allowing for rapid question-answer processing.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1166-1176
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• 1999

The spationtemporal databases support a historical informations as well as spatial managements for various kinds of objects in the real world, and can be efficiently used in many applications such as geographic information system, urban plan system, car navigation system. However it is difficult to represent efficiently historical operations with conventional database query language for spatial objects. In terms of cost for query processing, it also degenerates performance of query processing because of syntactic limitations which is innate in conventional query representation. So in this paper, we introduce a new query language, entitled as STQL, which has been extended on the basis of the most popular relational database query language SQL. And we implement as well as evaluate a spationtemporal query processing system that get a query written by STQL and then process it in a main memory.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.30-42
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• 2015

In this paper, we propose a new skyline query processing scheme to enhance accuracy of query processing and communication cost in mobile P2P environments. The proposed scheme consists of three stages such as the pre-skyline processing, the query transmission range extension policy, and the continuous skyline query processing. In the pre-skyline processing, a peer selects the candidate filtering objects who have the potential to be selected. By doing so, the proposed scheme reduces the filtering cost when processing the query. In the query transmission range extension policy, we have improved the accuracy by extending the query transmission range. In addition, it can handle continuous skyline query by performing the monitoring after the first skyline query processing. In order to show the superiority of the proposed method, we compare it with the existing schemes through performance evaluation. As a result, it was shown that the proposed scheme outperforms the existing schemes.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.107-116
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• 2012

The applying of semantic technologies that aim to let computers understand and automatically process the meaning of the interlinked data on the Web is spreading. In Semantic Web, understanding and accessing the associations between data that is, the meaning between data as well as accessing to the data itself is important. W3C recommended RDF (Resource Description Framework) as a standard format to represent both Semantic Web data and their associations and also proposed several RDF query languages in order to support query processing for RDF data. However further researches on the query language definition considering the semantic associations and query processing techniques are still required. In this paper, using the suffix array-based indexing scheme previously introduced for RDF query processing, we propose a query processing approach to handle ${\rho}$-path query which is the representative type of semantic associations. To evaluate the query processing performance of the proposed approach, we implemented two different types of query processing approaches and measured the average query processing times. The experiments show that the proposed approach achieved 1.8 to 2.5 and 3.8 to 11 times better performance respectively than others two.

• 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.