| Title |
Skewness-aware clustering tree for unevenly distributed spatial sensor nodes in smart city |
| ID_Doc |
38781 |
| Authors |
Tang, JN; Zhou, ZB; Shu, L; Niu, JW; Liu, J; Hu, QP; Wang, Q |
| Title |
Skewness-aware clustering tree for unevenly distributed spatial sensor nodes in smart city |
| Year |
2013 |
| Published |
International Journal Of Communication Systems, 26, 9 |
| Abstract |
Efficient spatial index is essential for querying spatial sensor nodes in the context of smart city. Sensor nodes are usually unevenly distributed in real situations. In this setting, R-tree and its variants may cause large overlap and coverage among branch nodes, which impact the query efficiency greatly. To address this challenge, this paper proposes a novel skewness-aware clustering tree (SWC-tree) by clustering sensor nodes. Sensor nodes in a dense region will be put into the same node. Thus, overlap and coverage among node regions are less than that of R-tree and its variants. As dense regions contain more sensor nodes, we assign a higher priority to these region nodes for facilitating the query operation. Experimental results show that in the context of skewed distribution, SWC-tree is efficient in performance for conducting insertion, deletion, and query operations of sensor nodes. Copyright (c) 2012 John Wiley & Sons, Ltd. |
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