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Parallel approach for processing itinerary-based RNN queries in object tracking WSNs

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Abstract

Reverse Nearest Neighbor (RNN) query is to find the set of objects that are closer to the Q than any other objects in dataset D. Owing to the wide application spectrum, there have been great demands for effective RNN query processing in the circumstance where the sensor nodes are deployed over a wide geographical area and track the location of objects. However, relentless energy and computing resource depletion are inevitable by the maintaining the infrastructures in the existing researches. Motivated by these issues, we propose a novel approach, named the parallel itinerary-based RNN (PIRNN) query processing algorithm which does not rely on any kind of infrastructures. PIRNN disseminates multiple itineraries concurrently and it prunes the search area to increase performance. Furthermore, we extend PIRNN with two optimization heuristics, called Peri-Segment Completion (PSC) and Look Forward (LF) to minimize the area to be searched. In order to evaluate the performance of PIRNN query processing, we compare PIRNN with itinerary-based SAA and TPL. The extensive simulation results show that the PIRNN method outperforms SAA and TPL in terms of network traffic.

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References

  1. Dyo, V., & Mascolo, C. (2005). Adaptive distributed indexing for spatial queries in sensor networks. In International workshop on database and expert systems applications (pp. 1103–1107). doi:10.1109/DEXA.2005.41.

    Google Scholar 

  2. Fu, T., Peng, W., & Lee, W. (2009). Parallelizing itinerary-based knn query processing in wireless sensor networks. IEEE Transactions on Knowledge and Data Engineering, 22, 711–729. doi:10.1109/TKDE.2009.146.

    Google Scholar 

  3. Gasarach, W. (2007). Review of “Research problems in discrete geometry by Brass, Moser, Pach”. SIGACT News, 38(4) 31–34. doi:10.1145/1345189.1345195.

    Article  Google Scholar 

  4. Hjaltason, G. R., & Samet, H. (1999). Distance browsing in spatial databases. ACM Transactions on Database Systems, 24(2), 265–318. doi:10.1145/320248.320255.

    Article  Google Scholar 

  5. Jin, G., & Nittel, S. (2008). Towards spatial window queries over continuous phenomena in sensor networks. IEEE Transactions on Parallel and Distributed Systems, 19(4), 559–571. doi:10.1109/TPDS.2007.70741.

    Article  Google Scholar 

  6. Korn, F., & Muthukrishnan, S. (2000). Influence sets based on reverse nearest neighbor queries. In Proceedings of the 2000 ACM SIGMOD international conference on management of data (SIGMOD ’00) (pp. 201–212). New York: ACM. doi:10.1145/342009.335415.

    Chapter  Google Scholar 

  7. Lin, C. Y., Peng, W. C., & Tseng, Y. C. (2006). Efficient in-network moving object tracking in wireless sensor networks. IEEE Transactions on Mobile Computing, 5(8), 1044–1056. doi:10.1109/TMC.2006.115.

    Article  Google Scholar 

  8. Demirbas, M., & Ferha, H. (2003). Peer-to-peer spatial queries in sensor networks. In Proceedings of third international conference on peer-to-peer computing (P2P 2003) (pp. 32–39).

    Chapter  Google Scholar 

  9. Mouratidis, K., Papadias, D., & Hadjieleftheriou, M. (2005). Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring. In Proceedings of the 2005 ACM SIGMOD international conference on management of data (SIGMOD ’05) (pp. 634–645). New York: ACM. doi:10.1145/1066157.1066230.

    Chapter  Google Scholar 

  10. Soheili, A., Kalogeraki, V., & Gunopulos, D. (2005). Spatial queries in sensor networks. In Proceedings of the 13th annual ACM international workshop on geographic information systems (GIS ’05) (pp. 61–70). New York: ACM. doi:10.1145/1097064.1097074.

    Google Scholar 

  11. Song, B., Cong, Y., Zhang, J., Li, X., & Yu, G. (2008). An effective approach for continuous window query in wireless sensor networks. In The 9th international conference for young computer scientists (ICYCS 2008) (pp. 504–509). doi:10.1109/ICYCS.2008.350.

    Chapter  Google Scholar 

  12. Stanoi, I., Agrawal, D., & Abbadi, A. E. (2000). Reverse nearest neighbor queries for dynamic databases. In ACM SIGMOD workshop on research issues in data mining and knowledge discovery (pp. 44–53).

    Google Scholar 

  13. Tao, Y., Papadias, D., & Lian, X. (2004). Reverse KNN search in arbitrary dimensionality. In Proceedings of the thirtieth international conference on very large data bases (VLDB ’04) (pp. 744–755). VLDB Endowment.

    Google Scholar 

  14. Tseng, Y. C., Chen, C. C., Lee, C., & Huang, Y. K. (2007). Incremental in-network RNN search in wireless sensor networks. In International conference on parallel processing workshops (ICPPW 2007) (pp. 64). doi:10.1109/ICPPW.2007.47.

    Google Scholar 

  15. Vlajic, N., & Xia, D. (2006). Wireless sensor networks: to cluster or not to cluster? In Proceedings of the 2006 international symposium on world of wireless, mobile and multimedia networks (WOWMOM ’06) (pp. 258–268). Washington: IEEE Comput. Soc. doi:10.1109/WOWMOM.2006.116.

    Chapter  Google Scholar 

  16. Winter, J., & Lee, W.-C. (2004). Wang-chien: KPT: a dynamic KNN query processing algorithm for location-aware sensor networks. In Proceedings of the 1st international workshop on data management for sensor networks (DMSN ’04) (pp. 119–124). New York: ACM. doi:10.1145/1052199.1052219.

    Google Scholar 

  17. Wu, S. H., Chuang, K. T., Chen, C. M., & Chen, M. S. (2007). DIKNN: an itinerary-based KNN query processing algorithm for mobile sensor networks. In IEEE 23rd international conference on data engineering (ICDE 2007) (pp. 456–465). doi:10.1109/ICDE.2007.367891.

    Chapter  Google Scholar 

  18. Wu, S. H., Chuang, K. T., Chen, C. M., & Chen, M. S. (2008). Toward the optimal itinerary-based KNN query processing in mobile sensor networks. IEEE Transactions on Knowledge and Data Engineering, 20(12), 1655–1668. doi:10.1109/TKDE.2008.80.

    Article  Google Scholar 

  19. Xu, J., Tang, X., & Lee, W. C. (2008). A new storage scheme for approximate location queries in object-tracking sensor networks. IEEE Transactions on Parallel and Distributed Systems, 19(2), 262–275. doi:10.1109/TPDS.2007.70740.

    Article  Google Scholar 

  20. Xu, Y., Fu, T. Y., Lee, W. C., & Winter, J. (2007). Processing k nearest neighbor queries in location-aware sensor networks. Signal Processing, 87(12), 2861–2881. doi:10.1016/j.sigpro.2007.05.013.

    Article  Google Scholar 

  21. Xu, Y., Lee, W. C., Xu, J., & Mitchell, G. (2006). Processing window queries in wireless sensor networks. In Proceedings of the 22nd international conference on data engineering (ICDE ’06) (p. 70). Washington: IEEE Computer Society. doi:10.1109/ICDE.2006.119.

    Google Scholar 

  22. Yao, Y., Tang, X., & Lim, E. P. (2006). In-network processing of nearest neighbor queries for wireless sensor networks. In Lecture notes in computer science: Vol. 3882. Database systems for advanced applications (pp. 35–49). Berlin/Heidelberg: Springer. http://www.springerlink.com/content/r40l4461w7631267/.

    Chapter  Google Scholar 

  23. Yao, Y., Tang, X., & Lim, E. P. (2009). Localized monitoring of KNN queries in wireless sensor networks. The VLDB Journal, 18(1), 99–117. doi:10.1007/s11235-013-9751-9.

    Article  Google Scholar 

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Correspondence to Jaehwa Chung.

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Chung, J., Jang, H., Jung, KH. et al. Parallel approach for processing itinerary-based RNN queries in object tracking WSNs. Telecommun Syst 55, 55–69 (2014). https://doi.org/10.1007/s11235-013-9751-9

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