Browse > Article

Efficient Processing of Aggregate Queries in Wireless Sensor Networks  

Kim, Joung-Joon (건국대학교 컴퓨터공학과)
Shin, In-Su (건국대학교 컴퓨터공학과)
Lee, Ki-Young (을지대학교 의료IT마케팅학과)
Han, Ki-Joon (건국대학교 컴퓨터공학과)
Publication Information
Spatial Information Research / v.19, no.3, 2011 , pp. 95-106 More about this Journal
Abstract
Recently as efficient processing of aggregate queries for fetching desired data from sensors has been recognized as a crucial part, in-network aggregate query processing techniques are studied intensively in wireless sensor networks. Existing representative in-network aggregate query processing techniques propose routing algorithms and data structures for processing aggregate queries. However, these aggregate query processing techniques have problems such as high energy consumption in sensor nodes, low accuracy of query processing results, and long query processing time. In order to solve these problems and to enhance the efficiency of aggregate query processing in wireless sensor networks, this paper proposes Bucket-based Parallel Aggregation(BPA). BPA divides a query region into several cells according to the distribution of sensor nodes and builds a Quad-tree, and then processes aggregate queries in parallel for each cell region according to routing. And it sends data in duplicate by removing redundant data, which, in turn, enhances the accuracy of query processing results. Also, BPA uses a bucket-based data structure in aggregate query processing, and divides and conquers the bucket data structure adaptively according to the number of data in the bucket. In addition, BPA compresses data in order to reduce the size of data in the bucket and performs data transmission filtering when each sensor node sends data. Finally, in this paper, we prove its superiority through various experiments using sensor data.
Keywords
Wireless Sensor Networks; Aggregate Query; Routing; Data Structure;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 S. Motegi, K. Yoshihara and H. Horiuchi, 2006, "DAG Based In-Network Aggregation for Sensor Network Monitoring," Proc. of the IEEE SAINT, pp.292-299.
2 D. Pendarakis, N. Shrivastava, L. Zhen and R. Ambrosio, 2007, "Information Aggregation and Optimized Actuation in Sensor Networks," Proc. of the IEEE Int. Conf. on Computer Communications, pp.2386-2390.
3 S. Roy, M. Conti, S. Setia and S. Jajodia, 2009, "Secure Median Computation in Wireless Sensor Networks," Journal of the Ad Hoc Networks, Vol.7 No.8, pp.1448-1462.   DOI   ScienceOn
4 Y. Xu, W. Lee, J. Xu and G. Mitchell, 2006, "Processing Window Queries in Wireless Sensor Networks," Proc. of the IEEE Int. Conf. on Data Engineering, pp.270-280.
5 강홍구, 김정준, 한기준, 2007, "데이타 중심 센서 네트워크에서 에너지 효율성을 고려한 비균등 네트워크 분할 기법," 한국공간정보시스템학회 논문지, 제9권 제3호, pp.35-50.
6 김정준, 심희정, 강홍구, 이기영, 한기준, 2009, "플래시 메모리 기반 효율적인 공간 인덱스," 한국공간정보시스템학회 논문지, 제11권 제2호, pp.133-142.
7 D. Culler and D. Estrin, 2004, "Overview of Sensor Networks," Journal of the IEEE Computer Magazine, Vol.37 No.8, pp.41-49.
8 E. Fasolo, M. Rossi, J. Widmer and M. Zorzi, 2007, "In-network Aggregation Techniques for Wireless Sensor Networks: a Survey," Journal of the IEEE Wireless Communications, Vol.14 No.2, pp.77-87.
9 J. J. Kim, H. K. Kang, D. S. Hong and K. J. Han, 2007, "An Efficient Compression Technique for a Multi-dimensional Index in Main Memory," Proc. of the Int. Conf. on Visual Information Systems, pp.336-346.
10 S. Madden, M. Franklin, J. Hellerstein and W. Hong, 2002, "TAG: A Tiny Aggregation Service for Ad-hoc Sensor Networks," Proc. of the Symposium on Operating System Design and Implementation, pp.131-146.
11 J. Li, F. Considine, G. Kollios and J. Byers, 2004, "Approximate Aggregation Techniques for Sensor Databases," Proc. of the ICDE, pp.449-460.