• Spatial Information Research
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• v.22 no.5
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• pp.9-18
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• 2014

According to the recent development of the ubiquitous computing environment, the use of spatio-temporal data from sensors with GPS is increasing, and studies on the Semantic Sensor Web using spatio-temporal data for providing different kinds of services are being actively conducted. Especially, the W3C developed the SSNO(Semantic Sensor Network Ontology) which uses sensor-related standards such as the SWE(Sensor Web Enablement) of OGC and defines classes and properties for expressing sensor data. Since these studies are available for the query processing about non-spatio-temporal sensor data, it is hard to apply them to spatio-temporal sensor data processing which uses spatio-temporal data types and operators. Therefore, in this paper, we developed the SWE based on SSNO which supports the spatio-temporal sensor data types and operators expanding spatial data types and operators in "OpenGIS Simple Feature Specification for SQL" by OGC. The system receives SensorML(Sensor Model Language) and O&M (Observations and Measurements) Schema and converts the data into SSNO. It also performs the efficient query processing which supports spatio-temporal operators and reasoning rules. In addition, we have proved that this system can be utilized for the web service by applying it to a virtual scenario.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.1017-1020
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• 2008

본 논문은 홈 센서 네트워크 환경내에서 구동되는 센서 및 이기종 장비들이 제공하는 서비스를 각 사용자가 원하는 조건에 맞추어 조합 및 변경을 해줄수 있는 시맨틱 웹을 활용하여 효율적인 네트워크 관리를 할 수 있도록 지능형 에이전트 시스템을 설계한다. 제안한 지능형 에이전트 시스템은 기존의 서비스뿐만 아니라 개인의 취향에 맞춘 서비스를 지원할 수 있다. 즉, 센서 네트워크가 쓰이고 있는 환경에서 각 센서나 장비들의 동작들을 지능형 에이전트를 통해서 사용자의 편의에 맞춰 제공한다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.634-636
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• 2004

유비쿼터스 환경에서는 어떤 기기나 사물에 센서와 같은 컴퓨팅이 가능한 기기를 집어넣어 언제, 어디서든 커뮤니케이션이 가능하게 한다. 이러한 기기나 사물간의 커뮤니케이션은 시맨틱 웹의 의미적 연관성을 이용하여 해결할 수 있다. 컴퓨터가 이해할 수 있는 의미적 연결을 하기 위해서는 온톨로지와 같은 시맨틱 웹 환경요소를 이용하여 정보자원들 간의 의미적 연결이 필요하다. 이틀 위해서 본 논문에서는 시맨틱 웹의 의미적 연관성을 이용하여 유비쿼터스 환경에서 컴퓨터가 스스로 정보자원들의 의미를 이해하고 동작할 수 있는 다중 에이전트 커뮤니케이션 구조를 제안한다. 본 논문에서 제안한 다중 에이전트 커뮤니케이션 구조는 에이전트들이 웹 온톨로지 언어를 기반으로 표현된 정보자원들 간의 연관성을 기반으로 자원의 의미론 이해하고. 기계들 사이에 커뮤니케이션이 가능하게 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.147-150
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• 2015

본 논문에서는 고성능 컴퓨팅 시스템의 성능 향상을 위한 효율적인 동적 작업부하 균등화 정책을 제안한다. 이 정책은 시스템 자원인 CPU와 메모리를 효율적으로 사용하여 고성능 컴퓨팅 시스템의 처리량을 최대화하고, 각 작업의 수행시간을 최소화한다. 또한 이 정책은 수행중인 작업의 메모리 요구량과 각 노드의 부하 상태를 파악하여 작업을 동적으로 할당한다. 이때 작업을 할당 받은 노드가 과부하 상태가 되면 다른 노드로 작업을 이주시켜 각 노드의 작업부하를 균등하게 유지함으로써 작업의 대기시간을 줄이고, 각 작업의 수행시간을 단축한다. 본 논문에서는 시뮬레이션을 통하여 제안하는 동적 작업부하 균등화 정책이 기존의 메모리 기반의 작업부하 균등화 정책에 비해 고성능 컴퓨팅 시스템의 성능 향상 면에서 우수함을 보인다.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.221-230
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• 2016

With emerging the Internet of Things (IoT) paradigm, the sensor network and sensor platform technologies have been changed according to exploding amount of sensors. Sensor Registry System (SRS) as a sensor platform is a system that registers and manages sensor metadata for consistent semantic interpretation in heterogeneous sensor networks. However, the SRS is unsuitable for the IoT environment. Therefore, this paper proposes sensor registry data model to register and manager sensor information in the IoT environment. We analyze Semantic Sensor Network Ontology (SSNO) for improving the existed SRS, and design metamodel based on the analysis result. We also build tables in a relational database using the designed metamodel, then implement SRS as a web application. This paper applies the SSNO and sensor ontology examples with translating into the proposed model in order to verify the suitability of the proposed sensor registry data model. As the evaluation result, the proposed model shows abundant expression of semantics by comparison with existed models.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.671-678
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• 2019

The semantic information provided through the semantic-based IoT system will produce new high value-added products that are completely different from what we have known and experienced. From this point of view, the key issue of current IoT technology and applications is the development of an intelligent IoT platform architecture. The proposed system collects the IoT data of the sensors from the cloud computer, converts them into RDF, and annotates them with semantics. The converted semantic data is shared and utilized through the ontology repository. We use KT's IoTMakers as a cloud computing environment, and the ontology repository uses Jena's Fuseki server to express SPARQL query results on the web using Daum Map API and Highcharts API. This gives people the opportunity to access the semantic IoT mash-up service easily and has various application possibilities.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.970-973
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• 2008

본 논문은 대체 서비스 디스커버리를 위한 효과 기반 명세 모델과 매칭 방식을 제안한다. 효과기반이라 함은 시맨틱 웹의 IOPE 모델에서 효과(effect)를 재 정의 하여 서비스 및 디바이스를 명세하는데 사용한다는 말이다. 여기서 효과는 인간이 인지할 수 있는 오감을 사용하며, 오감의 인지는 센서를 통하여 한다. 오감을 이용하여 서비스를 탐색 함으로써, 우리는 서비스의 가용성을 높일 수 있다. 매칭은 서비스를 세 가지의 타입으로 나눈 후 각 타입에 해당하는 항목별로 유사도를 계산하고 각 항목들의 합으로 최종 유사도를 도출해 낸다. 본 연구에서 제안한 효과 기반 서비스 디스커버리는 기존의 시맨틱 서비스 디스커버리보다 서비스의 가용성을 높여 줄 것으로 기대한다.

• Journal of KIISE
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• v.41 no.9
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• pp.686-698
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• 2014

Recently, large-scale streaming sensor data have emerged due to explosive supply of smart phones, diffusion of IoT and Cloud computing technology, and generalization of IoT devices. Also, researches on combination of semantic web technology are being actively pushed forward by increasing of requirements for creating new value of data through data sharing and mash-up in large-scale environments. However, we are faced with big issues due to large-scale and streaming data in the inference field for creating a new knowledge. For this reason, we propose the RDFS rule based parallel reasoning scheme to service by processing large-scale streaming sensor data with the semantic web technology. In the proposed scheme, we run in parallel each job of Rete network algorithm, the existing rule inference algorithm and sharing data using the HBase, a hadoop database, as a public storage. To achieve this, we implement our system and evaluate performance through the AWS data of the weather center as large-scale streaming sensor data.

• Information Systems Review
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• v.12 no.2
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• pp.89-104
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• 2010

Recently, ubiquitous sensor network (USN) has been applied to many areas including environment monitoring. A few studies applied the USN to disaster prevention and emergency management, in particular, aiming to conserve cultural heritage. USN is an useful technology to do online real-time monitoring for the purpose of early detection of the fire which is a critical cause of damage and destruction of cultural heritages. It is necessary to online monitor the cultural heritages that human has a difficulty to access or their external appearance and beauty are important, by using the USN. However, there exists false warning from USN-based monitoring systems without human intervention. In this paper, we presented an alternative to resolve the problem by applying ontology. Our intelligent fire early detection systems for conserving cultural heritages are based on ontology and inference rules, and tested under laboratory environments.