Spatial Indexing for Data Searching in Mobile Sensing Environments
Data searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. The problem in fact has been well studied for data generated by sensors that are installed at fixed locations; how...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/17/6/1427 |
| _version_ | 1798043536178806784 |
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| author | Yuchao Zhou Suparna De Wei Wang Klaus Moessner Marimuthu S. Palaniswami |
| author_facet | Yuchao Zhou Suparna De Wei Wang Klaus Moessner Marimuthu S. Palaniswami |
| author_sort | Yuchao Zhou |
| collection | DOAJ |
| description | Data searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. The problem in fact has been well studied for data generated by sensors that are installed at fixed locations; however, challenges emerge along with the popularity of opportunistic sensing applications in which mobile sensors keep reporting observation and measurement data at variable intervals and changing geographical locations. To address these challenges, we develop the Geohash-Grid Tree, a spatial indexing technique specially designed for searching data integrated from heterogeneous sources in a mobile sensing environment. Results of the experiments on a real-world dataset collected from the SmartSantander smart city testbed show that the index structure allows efficient search based on spatial distance, range and time windows in a large time series database. |
| first_indexed | 2024-04-11T22:50:25Z |
| format | Article |
| id | doaj.art-07a6a3a68f634bd2832baea51dc7f6c3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T22:50:25Z |
| publishDate | 2017-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-07a6a3a68f634bd2832baea51dc7f6c32022-12-22T03:58:36ZengMDPI AGSensors1424-82202017-06-01176142710.3390/s17061427s17061427Spatial Indexing for Data Searching in Mobile Sensing EnvironmentsYuchao Zhou0Suparna De1Wei Wang2Klaus Moessner3Marimuthu S. Palaniswami4Institute for Communication Systems (ICS), University of Surrey, Guildford GU2 7XH, UKInstitute for Communication Systems (ICS), University of Surrey, Guildford GU2 7XH, UKDepartment of Computer Science and Software Engineering, Xi’an Jiaotong-Liverpool University, Ren’ai Road Dushu Lake Higher Education Town SIP, Suzhou 215123, ChinaInstitute for Communication Systems (ICS), University of Surrey, Guildford GU2 7XH, UKDepartment of Electrical and Electronic Engineering, University of Melbourne, Parkville, VIC 3010, AustraliaData searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. The problem in fact has been well studied for data generated by sensors that are installed at fixed locations; however, challenges emerge along with the popularity of opportunistic sensing applications in which mobile sensors keep reporting observation and measurement data at variable intervals and changing geographical locations. To address these challenges, we develop the Geohash-Grid Tree, a spatial indexing technique specially designed for searching data integrated from heterogeneous sources in a mobile sensing environment. Results of the experiments on a real-world dataset collected from the SmartSantander smart city testbed show that the index structure allows efficient search based on spatial distance, range and time windows in a large time series database.http://www.mdpi.com/1424-8220/17/6/1427mobile sensor data searchopportunistic sensingmobile sensingspatial indexingWeb of Things (WoT) |
| spellingShingle | Yuchao Zhou Suparna De Wei Wang Klaus Moessner Marimuthu S. Palaniswami Spatial Indexing for Data Searching in Mobile Sensing Environments Sensors mobile sensor data search opportunistic sensing mobile sensing spatial indexing Web of Things (WoT) |
| title | Spatial Indexing for Data Searching in Mobile Sensing Environments |
| title_full | Spatial Indexing for Data Searching in Mobile Sensing Environments |
| title_fullStr | Spatial Indexing for Data Searching in Mobile Sensing Environments |
| title_full_unstemmed | Spatial Indexing for Data Searching in Mobile Sensing Environments |
| title_short | Spatial Indexing for Data Searching in Mobile Sensing Environments |
| title_sort | spatial indexing for data searching in mobile sensing environments |
| topic | mobile sensor data search opportunistic sensing mobile sensing spatial indexing Web of Things (WoT) |
| url | http://www.mdpi.com/1424-8220/17/6/1427 |
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