Distributed and Parallel Path Query Processing for Semantic Sensor Networks
As the sensor networks are broadly used in diverse range of applications, Semantic Web technologies have been adopted as a means to manage the huge amount of heterogeneous sensor nodes and their observation data. Large amount of sensor data are annotated with spatial, temporal, and thematic semantic...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2014-01-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/438626 |
| _version_ | 1797706599928692736 |
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| author | Sung-Jae Jung Dong-Min Seo Seungwoo Lee Hwan-Min Kim Hanmin Jung |
| author_facet | Sung-Jae Jung Dong-Min Seo Seungwoo Lee Hwan-Min Kim Hanmin Jung |
| author_sort | Sung-Jae Jung |
| collection | DOAJ |
| description | As the sensor networks are broadly used in diverse range of applications, Semantic Web technologies have been adopted as a means to manage the huge amount of heterogeneous sensor nodes and their observation data. Large amount of sensor data are annotated with spatial, temporal, and thematic semantic metadata. As a consequence, efficient query processing over large RDF graph is becoming more important in retrieving contextual information from semantic sensor data. In this paper we propose a novel path querying scheme which uses RDF schema information. By utilizing the class path expressions precalculated from RDF schema, the graph search space is significantly reduced. Compared with the conventional BFS algorithm, the proposed algorithm (bidirectional BFS combined with class path lookup approach) achieves performance improvement by 3 orders of magnitude. Additionally, we show that the proposed algorithm is efficiently parallelizable, and thus, the proposed algorithm returns graph search results within a reasonable response time on even much larger RDF graph. |
| first_indexed | 2024-03-12T05:53:44Z |
| format | Article |
| id | doaj.art-a8787d511eca4240b41e2aa532faf8df |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T05:53:44Z |
| publishDate | 2014-01-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-a8787d511eca4240b41e2aa532faf8df2023-09-03T04:50:48ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772014-01-011010.1155/2014/438626438626Distributed and Parallel Path Query Processing for Semantic Sensor NetworksSung-Jae Jung0Dong-Min Seo1Seungwoo Lee2Hwan-Min Kim3Hanmin Jung4 Department of Knowledge and Information Science, University of Science and Technology, Korea (UST), 217 Gajeong-ro, Yuseong-gu, Daejeon 305-350, Republic of Korea Department of Computer Intelligence Research, Korea Institute of Science and Technology Information (KISTI), 245 Daehak-ro, Yuseong-gu, Daejeon 305-806, Republic of Korea Department of Computer Intelligence Research, Korea Institute of Science and Technology Information (KISTI), 245 Daehak-ro, Yuseong-gu, Daejeon 305-806, Republic of Korea Department of Computer Intelligence Research, Korea Institute of Science and Technology Information (KISTI), 245 Daehak-ro, Yuseong-gu, Daejeon 305-806, Republic of Korea Department of Knowledge and Information Science, University of Science and Technology, Korea (UST), 217 Gajeong-ro, Yuseong-gu, Daejeon 305-350, Republic of KoreaAs the sensor networks are broadly used in diverse range of applications, Semantic Web technologies have been adopted as a means to manage the huge amount of heterogeneous sensor nodes and their observation data. Large amount of sensor data are annotated with spatial, temporal, and thematic semantic metadata. As a consequence, efficient query processing over large RDF graph is becoming more important in retrieving contextual information from semantic sensor data. In this paper we propose a novel path querying scheme which uses RDF schema information. By utilizing the class path expressions precalculated from RDF schema, the graph search space is significantly reduced. Compared with the conventional BFS algorithm, the proposed algorithm (bidirectional BFS combined with class path lookup approach) achieves performance improvement by 3 orders of magnitude. Additionally, we show that the proposed algorithm is efficiently parallelizable, and thus, the proposed algorithm returns graph search results within a reasonable response time on even much larger RDF graph.https://doi.org/10.1155/2014/438626 |
| spellingShingle | Sung-Jae Jung Dong-Min Seo Seungwoo Lee Hwan-Min Kim Hanmin Jung Distributed and Parallel Path Query Processing for Semantic Sensor Networks International Journal of Distributed Sensor Networks |
| title | Distributed and Parallel Path Query Processing for Semantic Sensor Networks |
| title_full | Distributed and Parallel Path Query Processing for Semantic Sensor Networks |
| title_fullStr | Distributed and Parallel Path Query Processing for Semantic Sensor Networks |
| title_full_unstemmed | Distributed and Parallel Path Query Processing for Semantic Sensor Networks |
| title_short | Distributed and Parallel Path Query Processing for Semantic Sensor Networks |
| title_sort | distributed and parallel path query processing for semantic sensor networks |
| url | https://doi.org/10.1155/2014/438626 |
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