• Journal of Computing Science and Engineering
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• v.3 no.1
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• pp.27-58
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• 2009

Aggregation join queries are an important class of queries over data streams. These queries involve both join and aggregation operations, with window-based joins followed by an aggregation on the join output. All existing research address join query optimization and aggregation query optimization as separate problems. We observe that, by putting them within the same scope of query optimization, more efficient query execution plans are possible through more versatile query transformations. The enabling idea is to perform aggregation before join so that the join execution time may be reduced. There has been some research done on such query transformations in relational databases, but none has been done in data streams. Doing it in data streams brings new challenges due to the incremental and continuous arrival of tuples. These challenges are addressed in this paper. Specifically, we first present a query processing model geared to facilitate query transformations and propose a query transformation rule specialized to work with streams. The rule is simple and yet covers all possible cases of transformation. Then we present a generic query processing algorithm that works with all alternative query execution plans possible with the transformation, and develop the cost formulas of the query execution plans. Based on the processing algorithm, we validate the rule theoretically by proving the equivalence of query execution plans. Finally, through extensive experiments, we validate the cost formulas and study the performances of alternative query execution plans.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.95-102
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• 2011

In this paper, a Mobile Continuous Query Processing System (MCQPS) is designed to solve problems related to database hoarding, maintenance of shared data consistency, and optimization of logging. These problems are caused by weak connectivity and disconnection of wireless networks inherent in mobile database systems under mobile client-server environments. We show the superiority of the proposed MCQPS by comparing its performance to the Client-Intercept-Server (C-I-S) model. In addition, several experimental results show the effectiveness of our proposed indexing structure and methodology for real-time continuous queries.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11B
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• pp.685-692
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• 2007

Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power, multi-functional sensors. A typical wireless sensor network (WSN) consists of a large number of sensor nodes that can measure and process data while communicating through wireless channels. In this paper, we propose a hybrid query processing (HQP) algorithm for user queries submitted to the WSN. Unlike previous algorithms that consider continuous queries only, HQP supports both continuous queries and ad-hoc queries. Specially. HQP tries to reduce energy consumption of ad-hoc queries by using query results cached at each sensor node which are created during the execution of the previous continuous query. HQP can also exploit a trade-off between energy consumption and data accuracy. We evaluate the performance of HQP under a variety of WSN configurations.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.715-717
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• 2003

Some previous works for nearest neighbor (NN) query processing technique can treat a case that query/data are both moving objects. However, they cannot find exact result owing to vagueness of criterion. In order to escape their limitations and get exact result, we propose new NN query techniques, exact CTNN (continuous trajectory NN) query, approximate CTNN query, and dynamic CTNN query. These are all superior to pervious works, by reducing of number of calculation, considering of trajectory information, and using of continuous query concept. Using these techniques, we can solve any situations and types of NN query in location-aware environment.

• ETRI Journal
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• v.29 no.5
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• pp.691-693
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• 2007

Existing methods to process continuous range queries are not scalable. In particular, as the number of continuous range queries on a large number of moving objects becomes larger, their performance degrades significantly. We propose a novel query indexing method called the projected attribute bit (PAB)-based query index. We project a two-dimensional continuous range query on each axis to get two one-dimensional bit lists. Since the queries are transformed to bit lists and query evaluation is performed by bit operations, the storage cost of indexing and query evaluation time are reduced significantly. Through various experiments, we show that our method outperforms the containment-encoded squares-based indexing method, which is one of the most recently proposed methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5042-5048
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• 2010

In ubiquitous environments, many continuous query processing techniques make use of operator network and sharing methods on continuous data stream generated from various sensors. Since similar continuous queries with the location information intensively occur in specific regions, we suggest a new operator sharing method based on grid partition for the spatial continuous query processing for location-based applications. Due to the proposed method shares moving objects by the given grid cell without sharing spatial operators individually, our approach can not only share spatial operators including similar conditions, but also increase the query processing performance and the utilization of memory by reducing the frequency of use of spatial operators.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.517-530
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• 2005

Researches for NN(nearest neighbor) query which is often used in LBS system, have been worked. However, Conventional NN query processing techniques are usually meaningless in moving object management system for LBS since their results may be invalidated as soon as the query and data objects move. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet continuous trajectory nearest neighbor query processing. The proposed technique consists of Approximate CTNN technique which has quick response time, and Exact CTNN technique which makes it possible to search accurately nearest neighbor objects. Experimental results using GSTD datasets showed that the Exact CTNN technique has high accuracy, but has a little low performance for response time. They also showed that the Approximate CTNN technique has low accuracy comparing with the Exact CTNN, but has high response time.

• Journal of Digital Convergence
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• v.3 no.1
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• pp.149-163
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• 2005

Researches for NN(nearest neighbor) query which is often used in LBS system, have been worked. However. Conventional NN query processing techniques are usually meaningless in moving object management system for LBS since their results may be invalidated as soon as the query and data objects move. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet continuous trajectory nearest neighbor query processing. The proposed technique consists of Approximate CTNN technique which has quick response time, and Exact CTNN technique which makes it possible to search accurately nearest neighbor objects. Experimental results using GSTD datasets shows that the Exact CTNN technique has high accuracy, but has a little low performance for response time. They also shows that the Approximate CTNN technique has low accuracy comparing with the Exact CTNN, but has high response time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2383-2389
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• 2011

Ubiquitous applications require hybrid continuous query processing which processes both on-line data stream and spatial data in the disk. In the hybrid continuous spatial query processing, disk access costs for the high-volume spatial data should be minimized. However, previous indexing methods cannot reduce the disk seek time, because it is difficult that the data are stored in contiguity with others. Also, existing methods for the space-filling curve considering data cluster have the problem which does not cluster available data for queries. Therefore, we propose the region storage structure for efficient data access in hybrid continues spatial query processing. This paper shows that there is an obvious improvement of query processing costs through the contiguous data storing method and the group processing for user queries based on the region storage structure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.441-443
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• 2010

Techniques for processing continuous queries are required to developing the various types of application services in ubiquitous environment where the real-time data acquisition from a lot of sensors, analysis, and processing are required. In the previous works of the continuous queries, they have represented all of the continuous queries as the interval queries or region queries, and proposed some methods for processing theses queries. The types of continuous queries, however, are very various, and could be presented by combining the attribute conditions, spatial conditions, and temporal conditions. In this paper, I have classify the types of continuous queries, and have proposed the continuous query model which could be presented by combining those conditions. The contributions of this paper include that it proposes the query model representing the continuous queries and suggests future research directions.