The Community for Technology Leaders
2007 IEEE 23rd International Conference on Data Engineering (2007)
Istanbul, Turkey
Apr. 15, 2007 to Apr. 20, 2007
ISBN: 1-4244-0802-4
pp: 456-465
Shan-Hung Wu , Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, ROC; Telcordia Applied Research Center, Taipei, Taiwan, ROC; Industrial Technology Research Institute, Hsinc
Kun-Ta Chuang , Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, ROC, doug@arbor.ee.ntu.edu.tw
Chung-Min Chen , Telcordia Applied Research Center, Taipei, Taiwan, ROC, chungmin@research.telcordia.com
Ming-Syan Chen , Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, ROC, mschen@cc.ee.ntu.edu.tw
ABSTRACT
Current approaches to K Nearest Neighbor (KNN) search in mobile sensor networks require certain kind of indexing support. This index could be either a centralized spatial index or an in-network data structure that is distributed over the sensor nodes. Creation and maintenance of these index structures, to reflect the network dynamics due to sensor node mobility, may result in long query response time and low battery efficiency, thus limiting their practical use. In this paper, we propose a maintenance-free, itinerary-based approach called Density-aware Itinerary KNN query processing (DIKNN). The DIKNN divides the search area into multiple cone-shape areas centered at the query point. It then performs a query dissemination and response collection itinerary in each of the cone-shape areas in parallel. The design of the DIKNN scheme also takes into account challenging issues such as the the dynamic adjustment of the search radius (in terms of number of hops) according to spatial irregularity or mobility of sensor nodes. The simulation results show that DIKNN yields substantially better performance and scalability over previous work, both as k increases and as the sensor node mobility increases. It outperforms the second runner with up to 50% saving in energy consumption and up to 40% reduction in query response time, while rendering the same level of query result accuracy.
INDEX TERMS
null
CITATION

K. Chuang, C. Chen, M. Chen and S. Wu, "DIKNN: An Itinerary-based KNN Query Processing Algorithm for Mobile Sensor Networks," 2007 IEEE 23rd International Conference on Data Engineering(ICDE), Istanbul, Turkey, 2007, pp. 456-465.
doi:10.1109/ICDE.2007.367891
317 ms
(Ver 3.3 (11022016))