Next Article in Journal
In-Situ Cure Monitoring of Wind Turbine Blades by Using Fiber Bragg Grating Sensors and Fresnel Reflection Measurement
Previous Article in Journal
Colorimetric Sensor Array for White Wine Tasting
Open AccessArticle

Distance-Constraint k-Nearest Neighbor Searching in Mobile Sensor Networks

Department of Computer Engineering, Kyung Hee University, Suwon 446-701, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard Reindl
Sensors 2015, 15(8), 18209-18228; https://doi.org/10.3390/s150818209
Received: 2 June 2015 / Revised: 17 July 2015 / Accepted: 22 July 2015 / Published: 27 July 2015
(This article belongs to the Section Sensor Networks)
The κ -Nearest Neighbors ( κNN) query is an important spatial query in mobile sensor networks. In this work we extend κNN to include a distance constraint, calling it a l-distant κ-nearest-neighbors ( l-κNN) query, which finds the κ sensor nodes nearest to a query point that are also at or greater distance from each other. The query results indicate the objects nearest to the area of interest that are scattered from each other by at least distance l. The l-κNN query can be used in most κNN applications for the case of well distributed query results. To process an l-κNN query, we must discover all sets of κNN sensor nodes and then find all pairs of sensor nodes in each set that are separated by at least a distance l. Given the limited battery and computing power of sensor nodes, this l-κNN query processing is problematically expensive in terms of energy consumption. In this paper, we propose a greedy approach for l-κNN query processing in mobile sensor networks. The key idea of the proposed approach is to divide the search space into subspaces whose all sides are l. By selecting κ sensor nodes from the other subspaces near the query point, we guarantee accurate query results for l-κNN. In our experiments, we show that the proposed method exhibits superior performance compared with a post-processing based method using the κNN query in terms of energy efficiency, query latency, and accuracy. View Full-Text
Keywords: wireless sensor networks; k-nearest-neighbors query; spatial queries wireless sensor networks; k-nearest-neighbors query; spatial queries
Show Figures

Figure 1

MDPI and ACS Style

Han, Y.; Park, K.; Hong, J.; Ulamin, N.; Lee, Y.-K. Distance-Constraint k-Nearest Neighbor Searching in Mobile Sensor Networks. Sensors 2015, 15, 18209-18228. https://doi.org/10.3390/s150818209

AMA Style

Han Y, Park K, Hong J, Ulamin N, Lee Y-K. Distance-Constraint k-Nearest Neighbor Searching in Mobile Sensor Networks. Sensors. 2015; 15(8):18209-18228. https://doi.org/10.3390/s150818209

Chicago/Turabian Style

Han, Yongkoo; Park, Kisung; Hong, Jihye; Ulamin, Noor; Lee, Young-Koo. 2015. "Distance-Constraint k-Nearest Neighbor Searching in Mobile Sensor Networks" Sensors 15, no. 8: 18209-18228. https://doi.org/10.3390/s150818209

Find Other Styles

Article Access Map by Country/Region

1
Only visits after 24 November 2015 are recorded.
Search more from Scilit
 
Search
Back to TopTop