Efficient Processing of Spatio-Temporal Joins on IoT Data
As the Internet of Things (IoT) has become widespread, the demand for storing and querying data generated by things (e.g., moving sensors) is growing to obtain more useful information. One of the emerging queries on such IoT data is the spatio-temporal join, which joins data generated by different t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9113316/ |
| _version_ | 1828928155517190144 |
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| author | Ki Yong Lee Minji Seo Ryong Lee Minwoo Park Sang-Hwan Lee |
| author_facet | Ki Yong Lee Minji Seo Ryong Lee Minwoo Park Sang-Hwan Lee |
| author_sort | Ki Yong Lee |
| collection | DOAJ |
| description | As the Internet of Things (IoT) has become widespread, the demand for storing and querying data generated by things (e.g., moving sensors) is growing to obtain more useful information. One of the emerging queries on such IoT data is the spatio-temporal join, which joins data generated by different things but generated at (almost) the same time and location. In this paper, we propose an efficient method for processing spatio-temporal joins on IoT data. The proposed method divides the 3D spatio-temporal space into small, equal-sized spaces, called cells. As data is generated by things, the proposed method maintains the information about which thing's data are in which cells. When a spatio-temporal join between specified things is requested, the proposed method first identifies cells, each of which has data of all the specified things within or near it. The proposed method then retrieves only the data within or near the identified cells and performs the join only between the retrieved data. Consequently, compared with previous methods where the processing cost increases rapidly as the size of data or the number of things being joined increases, the processing cost is greatly reduced. The experimental results on a real IoT dataset show that the proposed method significantly reduces the execution time compared with the existing methods. |
| first_indexed | 2024-12-14T00:00:16Z |
| format | Article |
| id | doaj.art-2e228117a31a490dbbad2378e79c6592 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T00:00:16Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2e228117a31a490dbbad2378e79c65922022-12-21T23:26:22ZengIEEEIEEE Access2169-35362020-01-01810837110838610.1109/ACCESS.2020.30012149113316Efficient Processing of Spatio-Temporal Joins on IoT DataKi Yong Lee0Minji Seo1Ryong Lee2https://orcid.org/0000-0001-5142-6106Minwoo Park3Sang-Hwan Lee4Department of Computer Science, Sookmyung Women's University, Seoul, South KoreaDepartment of Computer Science, Sookmyung Women's University, Seoul, South KoreaScientific Data Research Center, Korea Institute of Science and Technology Information, Daejeon, South KoreaScientific Data Research Center, Korea Institute of Science and Technology Information, Daejeon, South KoreaScientific Data Research Center, Korea Institute of Science and Technology Information, Daejeon, South KoreaAs the Internet of Things (IoT) has become widespread, the demand for storing and querying data generated by things (e.g., moving sensors) is growing to obtain more useful information. One of the emerging queries on such IoT data is the spatio-temporal join, which joins data generated by different things but generated at (almost) the same time and location. In this paper, we propose an efficient method for processing spatio-temporal joins on IoT data. The proposed method divides the 3D spatio-temporal space into small, equal-sized spaces, called cells. As data is generated by things, the proposed method maintains the information about which thing's data are in which cells. When a spatio-temporal join between specified things is requested, the proposed method first identifies cells, each of which has data of all the specified things within or near it. The proposed method then retrieves only the data within or near the identified cells and performs the join only between the retrieved data. Consequently, compared with previous methods where the processing cost increases rapidly as the size of data or the number of things being joined increases, the processing cost is greatly reduced. The experimental results on a real IoT dataset show that the proposed method significantly reduces the execution time compared with the existing methods.https://ieeexplore.ieee.org/document/9113316/Spatio-temporal joinspatio-temporal indexInternet of ThingsIoT data |
| spellingShingle | Ki Yong Lee Minji Seo Ryong Lee Minwoo Park Sang-Hwan Lee Efficient Processing of Spatio-Temporal Joins on IoT Data IEEE Access Spatio-temporal join spatio-temporal index Internet of Things IoT data |
| title | Efficient Processing of Spatio-Temporal Joins on IoT Data |
| title_full | Efficient Processing of Spatio-Temporal Joins on IoT Data |
| title_fullStr | Efficient Processing of Spatio-Temporal Joins on IoT Data |
| title_full_unstemmed | Efficient Processing of Spatio-Temporal Joins on IoT Data |
| title_short | Efficient Processing of Spatio-Temporal Joins on IoT Data |
| title_sort | efficient processing of spatio temporal joins on iot data |
| topic | Spatio-temporal join spatio-temporal index Internet of Things IoT data |
| url | https://ieeexplore.ieee.org/document/9113316/ |
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