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Spatial Indexing for Data Searching in Mobile Sensing Environments

Zhou, Yuchao, De, Suparna, Wang, Wei, Moessner, Klaus and Palaniswami, MS (2017) Spatial Indexing for Data Searching in Mobile Sensing Environments Sensors.

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Abstract

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.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Zhou, Yuchaoyuchao.zhou@surrey.ac.ukUNSPECIFIED
De, SuparnaS.De@surrey.ac.ukUNSPECIFIED
Wang, WeiUNSPECIFIEDUNSPECIFIED
Moessner, KlausK.Moessner@surrey.ac.ukUNSPECIFIED
Palaniswami, MSUNSPECIFIEDUNSPECIFIED
Date : 18 May 2017
Identification Number : 10.3390/s17061427
Copyright Disclaimer : © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Depositing User : Melanie Hughes
Date Deposited : 23 Jun 2017 07:58
Last Modified : 23 Jun 2017 07:58
URI: http://epubs.surrey.ac.uk/id/eprint/841473

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