Routing Techniques for Data Aggregation in Sensor Networks


Jeong-Joon Kim, Journal of Information Processing Systems Vol. 14, No. 2, pp. 396-417, Apr. 2018  

10.3745/JIPS.04.0065
Keywords: Itinerary, R-tree, Routing, Sensor Networks, Spatio-Temporal Data
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Abstract

GR-tree and query aggregation techniques have been proposed for spatial query processing in conventional spatial query processing for wireless sensor networks. Although these spatial query processing techniques consider spatial query optimization, time query optimization is not taken into consideration. The index reorganization cost and communication cost for the parent sensor nodes increase the energy consumption that is required to ensure the most efficient operation in the wireless sensor node. This paper proposes itinerary-based R-tree (IR-tree) for more efficient spatial-temporal query processing in wireless sensor networks. This paper analyzes the performance of previous studies and IR-tree, which are the conventional spatial query processing techniques, with regard to the accuracy, energy consumption, and query processing time of the query results using the wireless sensor data with Uniform, Gauss, and Skew distributions. This paper proves the superiority of the proposed IR-tree-based space-time indexing.


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Cite this article
[APA Style]
Jeong-Joon Kim (2018). Routing Techniques for Data Aggregation in Sensor Networks. Journal of Information Processing Systems, 14(2), 396-417. DOI: 10.3745/JIPS.04.0065.

[IEEE Style]
J. Kim, "Routing Techniques for Data Aggregation in Sensor Networks," Journal of Information Processing Systems, vol. 14, no. 2, pp. 396-417, 2018. DOI: 10.3745/JIPS.04.0065.

[ACM Style]
Jeong-Joon Kim. 2018. Routing Techniques for Data Aggregation in Sensor Networks. Journal of Information Processing Systems, 14, 2, (2018), 396-417. DOI: 10.3745/JIPS.04.0065.