The Community for Technology Leaders
RSS Icon
Issue No.12 - December (2008 vol.20)
pp: 1655-1668
Shan-Hung Wu , National Taiwan University, Taipei, Taiwan
Kun-Ta Chuang , National Taiwan University, Taipei, Taiwan
Chung-Min Chen , National Taiwan University, Taipei, Taiwan
Ming-Syan Chen , National Taiwan University, Taipei, Taiwan
Current approaches to K Nearest Neighbor (KNN) search in mobile sensor networks require certain kind of indexing support. 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. 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 takes into account several challenging issues such as the tradeoff between degree of parallelism and network interference on query response time, and the dynamic adjustment of the search radius (in terms of number of hops) according to spatial irregularity or mobility of sensor nodes. This model is validated by extensive simulations. 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.
Database Management, Information Storage and Retrieval, Query processing
Shan-Hung Wu, Kun-Ta Chuang, Chung-Min Chen, Ming-Syan Chen, "Toward the Optimal Itinerary-Based KNN Query Processing in Mobile Sensor Networks", IEEE Transactions on Knowledge & Data Engineering, vol.20, no. 12, pp. 1655-1668, December 2008, doi:10.1109/TKDE.2008.80
[1] U.D. of TraNsportation, “Intelligent Transportation System Joint Program Office Home,” http:/, 2006.
[2] P. Juang, H. Oki, Y. Wang, M. Martonosi, L. Peh, and D. Rubenstein, “Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with Zebranet,” Proc. 10th Int'l Conf. Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2002.
[3] F. of Am. Scientists, “Remote Battlefield Sensor System (Rembass),” http:/, 2000.
[4] H. Ferhatosmanoglu, E. Tuncel, D. Agrawal, and A. Abbadi, “Approximate Nearest Neighbor Searching in Multimedia Databases,” Proc. IEEE Int'l Conf. Data Eng. (ICDE), 2001.
[5] A.A.H.D. Chon and D. Agrawal, “Range and KNN Query Processing for Moving Objects in Grid Model,” Mobile Networks and Applications, vol. 8, no. 4, 2003.
[6] N. Roussopoulos, S. Kelley, and F. Vincent, “Nearest Neighbor Queries,” Proc. ACM SIGMOD, 1995.
[7] Z. Song and N. Roussopoulos, “K-Nearest Neighbor Search for Moving Query Point,” Proc. Int'l Symp. Spatial and Temporal Databases (SSTD), 2001.
[8] M.-S. Chen, P.S. Yu, and K.-L. Wu, “Optimizing Index Allocation for Sequential Data Broadcasting in Wireless Mobile Computing,” IEEE Trans. Knowledge and Data Eng., vol. 15, no. 1, pp. 161-173, Jan./Feb. 2003.
[9] W. Lee and B. Zheng, “DSI: A Fully Distributed Spatial Index for Location-Based Wireless Broadcast Services,” Proc. Int'l Conf. Distributed Computing Systems (ICDCS), 2005.
[10] B. Liu, W. Lee, and D. Lee, “Distributed Caching of Multi-Dimensional Data in Mobile Environments,” Proc. Int'l Conf. Mobile Data Management (MDM), 2005.
[11] J. Winter and W. Lee, “KPT: A Dynamic KNN Query Processing Algorithm for Location-Aware Sensor Networks,” Proc. Int'l Workshop Data Management for Sensor Networks (DMSN), 2004.
[12] J. Winter, Y. Xu, and W. Lee, “Energy Efficient Processing of k Nearest Neighbor Queries in Location-Aware Sensor Networks,” Proc. Ann. Int'l Conf. Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous), 2005.
[13] A. Guttman, “R-Trees: A Dynamic Index Structure for Spatial Searching,” Proc. ACM SIGMOD, 1984.
[14] G. Hjaltason and H. Samet, “Distance Browsing in Spatial Databases,” ACM Trans. Database Systems, vol. 24, no. 2, 1999.
[15] M. Mokbel, X. Xiong, and W. Aref, “SINA: Scalable Incremental Processing of Continuous Queries in Spatio-Temporal Databases,” Proc. ACM SIGMOD, 2004.
[16] IEEE Std. 802.15.4-2003, Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low Rate Wireless Personal Area Networks, 2003.
[17] IEEE Std. 802.11-1997, IEEE Standard for Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, 1997.
[18] M. Bawa, A. Gionis, H.G. Molina, and R. Motwani, “The Price of Validity in Dynamic Networks,” Proc. ACM SIGMOD, 2004.
[19] Y. Xu, W. Lee, J. Xu, and G. Mitchell, “Processing Window Queries in Wireless Sensor Networks,” Proc. IEEE Int'l Conf. Data Eng. (ICDE), 2006.
[20] M. Demirbas and H. Ferhatosmanoglu, “Peer-to-Peer Spatial Queries in Sensor Networks,” Proc. Int'l Conf. Peer-to-Peer Computing (ICP2PC), 2003.
[21] C. Intanagonwiwat, R. Govindan, and D. Estrin, “Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks,” Proc. ACM MobiCom, 2000.
[22] J. Kahn, R. Katz, and K. Pister, “Next Century Challenges: Mobile Networking for Smart Dust,” Proc. ACM MobiCom, 1999.
[23] R. Cheng, B. Kao, S. Prabhakar, A. Kwan, and Y. Tu, “Adaptive Stream Filters for Entity-Based Queries with Non-Value Tolerance,” Proc. Int'l Conf. Very Large Data Bases (VLDB), 2005.
[24] D. Niculescu and B. Nath, “Trajectory Based Forwarding and Its Applications,” Proc. ACM MobiCom, 2003.
[25] S. Patil, S. Das, and A. Nasipuri, “Serial Data Fusion Using Space-Filling Curves in Wireless Sensor Networks,” Proc. Conf. Sensor and Ad Hoc Comm. and Networks (SECON), 2004.
[26] C. Gui and P. Mohapatra, “Virtual Patrol: A New Power Conservation Design for Surveillance Using Sensor Networks,” Proc. Int'l Symp. Information Processing in Sensor Networks (IPSN), 2005.
[27] B. Karp and H. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks,” Proc. ACM MobiCom, 2000.
[28] F. Kuhn, R. Wattenhofer, Y. Zhang, and A. Zollinger, “Geometric Ad-Hoc Routing: Of Theory and Practice,” Proc. Ann. ACM Symp. Principles of Distributed Computing (PODC), 2003.
[29] Y. Kim, R. Govindan, B. Karp, and S. Shenker, “On the Pitfalls of Geographic Face Routing,” Proc. Discrete Algorithms and Methods for Mobile Computing and Comm. (DIALM), 2005.
[30] F. Kuhn, R. Wattenhofer, and A. Zollinger, “Worst-Case Optimal and Average-Case Efficient Geometric Ad-Hoc Routing,” Proc. ACM MobiHoc, 2003.
[31] D. Ganesan, S. Ratnasamy, H. Wang, and D. Estrin, “Coping with Irregular Spatio-Temporal Sampling in Sensor Networks,” ACM SIGCOMM Computer Comm. Rev., vol. 34, no. 1, 2004.
[32] G. Bianchi, “Performance Analysis of the IEEE 802.11 Distributed Coordination Function,” IEEE J. Selected Areas in Comm., vol. 18, no. 3, 2000.
[33] The Network Simulator,, 2000.
[34] I. Howitt and J. Gutierrez, “IEEE 802.15.4 Low Rate—Wireless Personal Area Network Coexistence Issues,” Wireless Comm. and Networking, vol. 3, nos. 16-20, 2003.
[35] “Caribou Population Distribution in Gros Morne National Park Greater Ecosystem,” sub/eco/itm5/fi-lr6caribou_E.asp, 2003.
43 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool