• 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.

• International Journal of Internet, Broadcasting and Communication
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• v.5 no.2
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• pp.1-4
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• 2013

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, RTLS (Real-Time Locating Services) dealing with spatio-temporal data is emerging as a promising technology. For these reasons, the ISO/IEC published RTLS standard specification for compatibility and interoperability in RTLS. Therefore, in this paper, we designed and implemented Spatio-temporal Query Processing Systems for efficiently managing and searching the incoming Spatio-temporal data stream of moving objects. Spatio-temporal Query Processing Systems's spatio-temporal middleware maintains interoperability among heterogeneous devices and guarantees data integrity in query processing through real time processing of unceasing spatio-temporal data streams and two way synchronization of spatio-temporal DBMSs. Web Server 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 spatio-temporal middleware.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.159-166
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• 2008

Recently, according to the rapid development of location positioning technology and wireless communications technology and increasement of usage of moving object data, many researches and developments on the real-time locating systems which provides real time service of moving object data stream are under proceeding. However, MO (Moving Object) DBMS used based system in the in these systems is the inefficient management of moving object data streams, and the existing DSMS (Data Stream Management System) has problems that spatio-temporal data are not handled efficiently. Therefore, in this thesis, we designed and implemented spatio-temporal DSMS for efficient real-time management of moving object data stream. This thesis implemented spatio-temporal DSMS based STREAM (STanford stREam dAta Manager) of Stanford University is supporting real-time management of moving object data stream and spatio-temproal query processing and filtering for reduce the input loading. Specifically, spatio-temporal operators of the spatio-temporal DSMS support standard interface of SQL form which extended "Simple Feature Specification for SQL" standard specifications presented by OGC for compatibility. Finally, implemented spatio-temporal DSMS in this thesis, proved the effectiveness of the system that as applied real-time monitoring areas that require real-time locating of object data stream DSMS.

• Spatial Information Research
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• v.18 no.1
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• pp.77-87
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• 2010

Spatio-temporal join operators are essential to the management of spatio-temporal data such as moving objects. For example, the join operators are parts of processing to analyze movement of objects and search similar patterns of moving objects. Various studies on spatio-temporal join queries in outdoor space have been done. Recently with advance of indoor positioning techniques, location based services are required in indoor space as well as outdoor space. Nevertheless there is no one about processing of spatio-temporal join query in indoor space. In this paper, we introduce continuous spatio-temporal self-join queries in indoor space and propose a method of processing of the join queries over stream data of moving objects. The continuous spatio-temporal self-join query is to update the joined result set satisfying spatio-temporal predicates continuously. We assume that positions of moving objects are represented by symbols such as a room or corridor. This paper proposes a data structure, called Candidate Pairs Buffer, to filter and maintain massive stream data efficiently and we also investigate performance of proposed method in experimental study.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.145-152
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• 2010

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, RTLS(Real-Time Locating Services) dealing with spatio-temporal data is emerging as a promising technology. For these reasons, the ISO/IEC published the RTLS standard specification for compatibility and interoperability in RTLS. Therefore, in this paper, we designed and implemented Spatio-temporal Query Processing Systems for efficiently managing and searching the incoming Spatio-temporal data stream of moving objects. Spatio-temporal Query Processing Systems's spatio-temporal middleware maintains interoperability among heterogeneous devices and guarantees data integrity in query processing through real time processing of unceasing spatio-temporal data streams and two way synchronization of spatio-temporal DBMSs. Web Server 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 spatio-temporal middleware. Finally, this thesis proved the utility of the system by applying the spatio-temporal Query Processing Systems to a real-time Locating Services.

• Spatial Information Research
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• v.16 no.2
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• pp.219-236
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• 2008

Data stream collected from sensors contain a large amount of useful information including causality relationships. The causality join query for data stream is to retrieve a set of pairs (cause, effect) from streams of data. A part of causality pairs may however be lost from the query result, due to the delay from sensors to a data stream management system, and the limited size of sliding windows. In this paper, we first investigate spatial, temporal, and spatio-temporal aspects of the causality join query for data stream. Second, we propose several strategies for sliding window management based on these observations. The accuracy of the proposed strategies is studied by intensive experiments, and the result shows that we improve the accuracy of causality join query in data stream from simple FIFO strategy.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.43-54
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• 2009

As R&D(Research and Development) is going on actively to develop technologies for the ubiquitous computing environment, which Is the human-oriented future computing environment, GIS dealing with spatio-temporal data is emerging as a promising technology. This also increases the necessity of the middleware for providing services to give interoperability in various heterogeneous environments. The core technologies of the middleware are real-time processing technology of data streams coming unceasingly from positioning systems and data stream processing technology developed for non-spatio-temporal data. However, it has problems in processing queries on spatio-temporal data efficiently. Accordingly, this paper designed and implemented the spatio-temporal middleware that provides interoperability between a mobile spatio-temporal DBMS(DataBase Management System) and a server spatio-temporal MMDBMS(Main Memory DataBase Management System). The spatio-temporal middleware maintains interoperability among heterogeneous devices and guarantees data integrity in query processing through real-time processing of unceasing spatio-temporal data streams and two way synchronization of spatio-temporal DBMSs. In addition, it manages session for the connection of each spatio-temporal DBMS and manages resources for its stable operation. Finally, this paper proved the usability of the spatio-temporal middleware by applying it to a real-time position tracking system.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.287-288
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• 2009

Multi-query optimization (MQO) is a critical research issue in the real-time data stream management system (DSMS). We propose to address this problem in the ubiquitous GIS (u-GIS) environment, focusing on grouping 'similar' spatio-temporal queries incrementally into N clusters so that they can be processed virtually as N queries. By minimizing N, the overlaps in the data requirements of the raw queries can be avoided, which implies the reducing of the total disk I/O cost. In this paper, we define the spatio-temporal query clustering problem and give a data cubing approach (Q-cube), which is expected to be implemented in the cloud computing paradigm.

• 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.