• Journal of the Korea Society of Computer and Information
• /
• v.13 no.1
• /
• pp.65-73
• /
• 2008

The telematics data management deals with queries on stream data coming from moving cars. So the stream DBMS should process the large amount of data stream in real-time. In this article, previous research projects are analyzed in the aspects of query processing. And a hybrid model is introduced where query preprocessor is used to process all types of queries in one singe system. Decreasing cost and rapidly increasing Performance of devices may guarantee the utmost parallelism of the hybrid system. As a result, various types of stream DBMS queries could be processed in a uniform and efficient way in a single system.

• Journal of KIISE:Databases
• /
• v.36 no.4
• /
• pp.280-291
• /
• 2009

Skyline Query processing is important to wireless sensor applications in order to process multi-dimensional data efficiently. Most skyline researches about sensor network focus on minimizing the energy consumption due to the battery powered constraints. In order to reduce energy consumption, Filtering Method is proposed. Most existing researches have assumed a snapshot skyline query processing and do not consider continuous queries and use data generated in ancestor node. In this paper, we propose an energy efficient method called Bottom up filtering tuple selection for continuous skyline query processing. Past skyline data generated in child nodes are stored in each sensor node and is used when choosing filtering tuple. We also extend the algorithms, called Support filtering tuple(SFT) that is used when we choose the additional filtering tuple. There is a temporal correlation between previous sensing data and recent sensing data. Thus, Based on past data, we estimate current data. By considering this point, we reduce the unnecessary communication cost. The experimental results show that our method outperforms the existing methods in terms of both data reduction rate(DRR) and total communication cost.

• The KIPS Transactions:PartD
• /
• v.15D no.3
• /
• pp.297-304
• /
• 2008

Due to the proliferation of the Internet and intranet, new application domains such as stream data processing have emerged. Stream data is real-timely and continuously generated. In stream data environments, a lot of queries are registered, and then, the arrived data item is evaluated by registered queries. Thus, to accelerate the query performance, diverse continuous query index schemes have been proposed for stream data processing systems. In this paper, we focus on the query index technique for stream data. In general, a stream query contains the range condition. Thus, by using range conditions, the queries can be indexed. In this paper, we propose an efficient query index scheme, called QUISIS, using a modified Interval Skip Lists to accelerate search time. QUISIS utilizes a locality where a value which will arrive in near future is similar to the current value. Through the experimental study, we show the efficiency of our proposed method.

• Journal of KIISE:Databases
• /
• v.34 no.2
• /
• pp.166-178
• /
• 2007

The ALE specification of EPCglobal is leading the development of RFID standards, includes the Event Cycle Specification (ECSpec) describing how long a cycle is, how to filter RFID tag data and which reader is interested in. The ECSpec is a specification for filtering and collecting RFID tag data. It is registered to a middleware for long time and is evaluated to return results satisfying the requirements included in it. Thus, it is quite similar to the continuous query. It can be transformed into a continuous query as its predicate in WHERE clause is characterized by the long interval. Long intervals cause problems deteriorating insertion and search performance of existing query indices. In this paper, we propose a TLC-index as a new query index structure for long interval data. The TLC-index has hybrid structure that uses the cell construct of CQI-index with the virtual construct of VCR-index for partitioning long intervals. The TLC-index can reduce the storage cost and improve the insertion performance through decomposing long intervals into one or more cell constructs that have long size. It can also improve the search performance through decomposing short intervals into one or more virtual constructs that have short size enough to fit into those intervals.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.11a
• /
• pp.413-416
• /
• 2008

In the presence of multiple continuous queries, multi-query optimizing is a new challenge to process multiple stream data in real-time. So, in this paper, we proposed an approach to optimize multi-query of sliding window on network traffic data streams and do some comparisons to traditional queries without optimizing. We also detail some method of scheduling on different data streams, while different scheduling made different results. We test the results on variety of multi-query processing schedule, and proofed the proposed method is effectively optimized the data stream similar multi-queries.

• Spatial Information Research
• /
• v.18 no.3
• /
• pp.53-62
• /
• 2010

Recent development in wireless communication technology, like GPS, and mobile equipments, like PDA and cellular phone, make location-based services (LBSs) popular. However, because, users continuously request a query to a server in the LBSs by using their exact locations, privacy information could be in danger. Therefore, a mechanism for users' privacy protection is required for the safe and comfortable use of LBSs by mobile users. For this, we, in this paper, propose a grid-based cloaking area creation scheme supporting continuous LBSs in peer-to-peer environment. The proposed scheme creates a cloaking area by using Chord protocol, so as to support the continuous LBSs in peer-to-peer environment. Finally, we show from a performance analysis that our cloaking scheme outperforms the existing cloaking schemes, in terms of service time.

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

• Spatial Information Research
• /
• v.15 no.2
• /
• pp.95-109
• /
• 2007

Recently people have been offered location based services on road networks. The navigation system, one of applications, serves to find the nearest gas station or guide divers to the shortest path based 2D map. However 3D map is more important media than 2D map to make sense friendly for the real. Although 3D map's data size is huge, portable devices' storage space is small. In this paper, we define continuous perspective queries to support 3D map to mobile user on road networks and propose this queries processing method.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.79-88
• /
• 2009

The volume of memory to store real-time data stream is varied dynamically. Continuous queries processing the data stream must manage the storage volume dynamically. In previous research, according to current volume of data a general memory manager which allocates and releases memory by a page unit is researched.However, the method frequently executes page allocation and release to store data stream. Moreover, particularly delayed queries can monopolize many of pages because the method directly allocates pages when a query has not enough memory. Focusing on the problems in memory management systems, this research proposes a memory management method which reduces the frequency of allocation and release and uniformly distributes pages for queries. The method can reduce the frequency of allocation and release through allocation based on utilization ratio of pages in each query and prevent memory monopoly through memory allocation which considers query delay.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.249-252
• /
• 2009

Recently, it is possible for users to acquire necessary data easily as the various schemes of the searching information are developed. Since these data rise continuously like stream data, it is required to extract the appropriate data for the user's needs from the mass data on the internet. In the traditional scheme, they are acquired by processing the user queries after the occurred data are stored at a database. However, it is inefficient to process the user queries over the large volume of continuous data by using the traditional scheme. In this paper, we propose the query processing scheme to extract the data efficiently for the user requirements from the large volume of continuous data. On the proposed scheme, we present the Event-Profile Model to define the data occurrence on the internet as the events and the user's requirements as the profiles. We also show the filtering scheme to process the events and the profiles efficiently.