Wan, S., Zhao, Y., Wang, T., Gu, Z., Abbasi, Q. H. and Choo, K.-K. R. (2019) Multi-dimensional data indexing and range query processing via Voronoi diagram for internet of things. Future Generation Computer Systems, 91, pp. 382-391. (doi: 10.1016/j.future.2018.08.007)
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Abstract
In a typical Internet of Things (IoT) deployment such as smart cities and Industry 4.0, the amount of sensory data collected from physical world is significant and wide-ranging. Processing large amount of real-time data from the diverse IoT devices is challenging. For example, in IoT environment, wireless sensor networks (WSN) are typically used for the monitoring and collecting of data in some geographic area. Spatial range queries with location constraints to facilitate data indexing are traditionally employed in such applications, which allows the querying and managing the data based on SQL structure. One particular challenge is to minimize communication cost and storage requirements in multi-dimensional data indexing approaches. In this paper, we present an energy- and time-efficient multidimensional data indexing scheme, which is designed to answer range query. Specifically, we propose data indexing methods which utilize hierarchical indexing structures, using binary space partitioning (BSP), such as kd-tree, quad-tree, k-means clustering, and Voronoi-based methods to provide more efficient routing with less latency. Simulation results demonstrate that the Voronoi Diagram-based algorithm minimizes the average energy consumption and query response time.
Item Type: | Articles |
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Additional Information: | This work is supported by the National Natural Science Foundation of China under Grant No. 61672454. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Abbasi, Professor Qammer |
Authors: | Wan, S., Zhao, Y., Wang, T., Gu, Z., Abbasi, Q. H., and Choo, K.-K. R. |
College/School: | College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
Journal Name: | Future Generation Computer Systems |
Publisher: | Elsevier |
ISSN: | 0167-739X |
ISSN (Online): | 1872-7115 |
Published Online: | 18 September 2018 |
Copyright Holders: | Copyright © 2018 Elsevier B.V. |
First Published: | First published in Future Generation Computer Systems 91: 382-391 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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