• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.9-16
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• 2009

In ubiquitous spatial computing environments, GeoSensor generates sensor data streams including spatial information as well as various conventional sensor data from RFID, WSN, Web CAM, Digital Camera, CCTV, and Telematics units. This GeoSensor enables the revitalization of various ubiquitous USN technologies and services on geographic information. In order to service the u-GIS applications based on GeoSensors, it is indispensable to efficiently process sensor data streams from GeoSensors of a wide area. In this paper, we propose a GeoSensor data stream processing system for u-GIS computing over real-time stream data from GeoSensors with geographic information. The proposed system provides efficient gathering, storing, and continuous query processing of GeoSensor data stream, and also makes it possible to develop diverse u-GIS applications meet each user requirements effectively.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.21-31
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• 2012

Recently, according to the development of ubiquitous computing technology, the efficient management of locations of moving objects is increasing rapidly in various fields. However, MODBMS and DSMS can not support the efficient real-time management of spatio-temporal stream data of moving objects. Therefore, this paper designed and implemented a spatio-temporal DSMS which can support the efficient real-time management of spatio-temporal stream data of moving objects. Especially, to develop the spatio-temporal DSMS, we extended STREAM of Stanford University and used GEOS that supports spatial data types and spatial operators of OGC. Finally, this paper proved the efficiency of the spatio-temporal DSMS by applying it to the real-time monitoring field which requires the real-time management of spatio-temporal stream data of moving objects.

• Journal of Korea Spatial Information System Society
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• v.8 no.1 s.16
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• pp.1-16
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• 2006

Recently, human based computing environment for supporting users to concentrate only user task without sensing other changes from users is being progressively researched and developed. But middleware deletes steream data processed for reducing process load of massive information from RFID sensor in this computing. So, this kind of middleware have problems when user demands probability or statistics needed for data warehousing or data mining and when user demands very important stream data repeatedly but already discarded in the middleware every former time. In this paper, we designs Sensor Middleware Architecture on Multi Level Spatial DBMS with Snapshot and manage repeatedly required stream datas to solve reusing problems of historical stream data in current middleware. This system uses disk databse that manages historical stream datas filtered in middleware for requiring services using historical stream information as data mining or data warehousing from user, and uses memory database that mamages highly reuseable data as a snapshot when stream data storaged in disk database has high reuse frequency from user. For the more, this system processes memory database management policy in a cycle to maintain high reusement and rapid service for users. Our paper system solves problems of repeated requirement of stream datas, or a policy decision service using historical stream data of current middleware. Also offers variant and rapid data services maintaining high data reusement of main memory snapshot datas.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.47-58
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• 2008

With the recent development of the ubiquitous computing technology, there are increasing interest and research in technologies such as sensors and RFID related to information recognition and location positioning in various ubiquitous fields. Especially, a standard specification was required for compatibility and interoperability in various RTLS(Real-Time Locating Systems) according to the development of RTLS to provide location and status information of moving objects using the RFID Tag. For these reasons, the ISO/IEC published the RTLS standard specification for compatibility and interoperability in RTLS. Therefore, in this paper, we designed and im plemented RTLS based on the spatial DSMS(Data Stream Management Stream) for efficiently managing and searching the incoming data stream of moving objects. The spatial DSMS is an extended system of STREAM(STanford stREam datA Manager) developed by Standford University to make various spatial operations possible. RTLS based on the spatial DSMS uses the SOAP(Simple Object Access Protocol) message between client and server for interoperability and translates client's SOAP message into CQL(Continuous Query Language) of the spatial DSMS. Finally, we proved the efficiency of RTLS based on the spatial DSMS by applying it for the staff location management service.

• Journal of KIISE
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• v.44 no.11
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• pp.1209-1218
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• 2017

A variety of sensors is widely used these days, and it has become much easier to acquire spatial big data streams from various sources. Since spatial data streams have inherently skewed and dynamically changing distributions, the system must effectively distribute the load among workers. Previous studies to solve this load imbalance problem are not directly applicable to processing spatial data. In this research, we propose Adaptive Spatial Key Grouping (ASKG). The main idea of ASKG is, by utilizing the previous distribution of the data streams, to adaptively suggest a new grouping scheme that evenly distributes the future load among workers. We evaluate the validity of the proposed algorithm in various environments, by conducting an experiment with real datasets while varying the number of workers, input rate, and processing overhead. Compared to two other alternative algorithms, ASKG improves the system performance in terms of load imbalance, throughput, and latency.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.27-33
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• 2009

The emergences of GeoSensor and researches about GIS have promoted many researches of u-GIS. The disaster application coupled in the u-GIS can apply to monitor accident area and to prevent spread of accident. The application needs the u-GIS DSMS technique to acquire, to process GeoSensor data and to integrate them with GIS data. The u-GIS DSMS must process big and large-volume data stream such as spatial data and multimedia data. Due to the feature of the data stream, in u-GIS DSMS, query processing can be delayed. Moreover, as increasing the input rate of data in the area generating events, the network traffic is increased. To solve this problem, in this paper we describe TRIGGER ACTION clause in CQ on the u-GIS DSMS environment and proposes data source management. Data source weight table controls GES information and incoming data rate. It controls incoming data rate as increasing weight at GES of disaster area. Consequently, it can contribute query processing rate and accuracy

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.535-544
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• 2018

As the spread of mobile devices equipped with various sensors and high-quality wireless network communications functionsexpands, the amount of spatio-temporal data generated from mobile devices in various service fields is rapidly increasing. In conventional research into processing a large amount of real-time spatio-temporal streams, it is very difficult to apply a Hadoop-based spatial big data system, designed to be a batch processing platform, to a real-time service for spatio-temporal data streams. This paper extends the MapReduce online framework to support real-time query processing for continuous-input, spatio-temporal data streams, and proposes a load management method to distribute overloads for efficient query processing. The proposed scheme shows a dynamic load balancing method for the nodes based on the inflow rate and the load factor of the input data based on the space partition. Experiments show that it is possible to support efficient query processing by distributing the spatial data stream in the corresponding area to the shared resources when load management in a specific area is required.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.177-186
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• 2013

The purpose of this study was to analyze the temporal and spatial characteristics of the stream flow of small rural streams for investigating the status of stream depletion located downstream of irrigation reservoir. Bonghyun and Hai reservoirs and each downstream were selected for this study. Streamflow was measured for 8 stations downstream from two reservoirs from 2010 to 2012. The water quality samples were collected monthly from the 8 stream stations and 2 reservoir stations from 2011 to 2012. The stream depletion was found in most of the downstream of reservoirs for the non-irrigation period and even in the irrigation period when there were a lot of antecedent precipitation. We found that the stream segments where there were few streamflow, vegetation covers the stream and block the streamflow which makes the stream lost its original function as a stream. Water quality monitoring results of Bonghyun stream indicated that the concentration of SS, Turbidity, TOC, COD were decreased as the stream flows from the reservoir to downstream while the TN and TP were increased. The correlation analysis for water quality data indicated that the correlation between T-N and T-P was high for Bonghyeon and Sukji streams, respectively. Continuous monitoring for rural streams located in downstream of reservoirs are required to quantify the status of stream flow depletion and determine the amount of environmental flows.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.97-102
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• 2008

A wireless sensor network consists of many sensors that collect and transmit physical or environmental conditions at different locations to a server continuously. Many researches mainly focus on processing continuous queries on real-time data stream. However, they do not concern the problem of storing the historical data, which is mandatory to the historical queries. In this paper, we propose two time-based storage methods to store the sensor data stream and reduce the managed tuples without any loss of information, which lead to the improvement of the accuracy of query results.