Open Access Open Access  Restricted Access Subscription or Fee Access

Dispensation Location-Dependent Queries in Portable Environments

R. Rathika, G. Deepthi Raj

Abstract


Caching legitimate districts of spatial queries at mobile clients is effective in reducing the number of queries submitted by wireless clients and query burden on the server although, wireless purchasers suffer from longer waiting time for the server to compute valid districts.We propose in this paper a proxy-based approach to continuous nearest-neighbor (NN) and window queries. The proxy conceivesapproximated valid regions (EVRs) for wireless purchasers by exploiting spatial and temporal locality of spatial queries. For NN queries, wedevelop two new algorithms to accelerate EVR development, premier the proxy to build effective EVRs even when the cache dimensionsis little. Onthe other hand, we suggest to comprise the EVRs of window queries in the pattern of vectors, called approximated window vectors (EWVs),to accomplish larger approximated legitimate districts. Thisinnovative representation and the affiliated creation algorithm outcome in more effectiveEVRs of window queries. In addition, due to the distinct characteristics, we use separate catalogue organisations, namely EVR-tree and gridcatalogue, for NN queries and window queries, respectively. To farther boost effectiveness, we develop algorithms to exploit the outcomes ofNN queries to help grid index growth, benefiting EWV creation of window queries. likewise, the grid catalogue is utilized to support NN query answering and EVR updating. We conduct several experiments for presentation evaluation. The untested results show that thesuggested approach considerably outperforms the living proxy-based approaches.

Keywords


Dispensation Location, Location based services (LBSs), location dependent data services (LDISs)

Full Text:

PDF

References


D. Lee, B. Zheng, and W.-C. Lee, “Data Management in position-reliant Information Services,” IEEE Pervasive Computing, vol. 1, no. 3, pp. 65-72, July-Sept. 2002.

B. Zheng, J. Xu, and D.L. Lee, “Cache Invalidation and Replacement Strategies for Location-Dependent Data in wireless Environments,” IEEE Trans. Computers, vol. 15, no. 10, pp. 1141-1153, Oct. 2002.

B. Zheng and D.L. Lee, “Processing Location-Dependent Queries in a Multi-Cell Wireless Environment,” Proc. Second ACM Int’lWorkshop Data Eng. for Wireless and wireless get access to, 2001.

B. Zheng, J. Xu, W.-C. Lee, and D.L. Lee, “On Semantic Caching and Query Scheduling for wireless Nearest-Neighbor Search, ”Wireless systems, vol. 10,no. 6, pp. 653-664,Dec. 2004

X. Gao and A. Hurson, “Location reliant Query Proxy,” Proc.ACM Int’l Symp. directed Computing, pp. 1120-1124, 2005.

X. Gao, J. Sustersic, and A.R. Hurson, “Window Query Processing with Proxy Cache,” Proc. Seventh IEEE Int’l Conf. wireless facts and figures Management, 2006.

K.C. Lee, J. Schiffman, B. Zheng, and W.-C. Lee, “Valid Scope Computation for Location-Dependent Spatial Query in Mobile announced Environments,” Proc. 17th ACM Conf. data and information administration, pp. 1231-1240, 2008.

K.C.K. Lee, W.-C. Lee, H.V. Leong, B. Unger, and B. Zheng,“Efficient legitimate Scope for Location-Dependent Spatial Queries inwireless Environments,” J. Software, vol. 5, no. 2, pp. 133-145, Feb.2010.

S. Prabhakar, Y. Xia, D.V. Kalashnikov, W.G. Aref, and S.E.Hambrusch, “Query Indexing and Velocity guarded Indexng:Scalable methods for relentless Queries on Moving Objects,”

Y. Cai, K.A. Hua, and G. Cao, “Processing Range-MonitoringQueries on Heterogeneous wireless Objects,” Proc. Fifth IEEE Int’lConf. wireless facts and figures Management, pp. 27-38, 2004.

B. Gedik and L. Liu, “Mobieyes: A Distributed positionMonitoring Service utilising going position Queries,” IEEE Trans.wireless Computing, vol. 5, no. 6, pp. 1384-1042, Oct. 2006.

H. Hu, J. Xu, and D.L. Lee, “A Generic structure for Monitoringrelentless Spatial Queries over going Objects,” Proc. ACMSIGMOD Int’l Conf. Management of Data, pp. 479-490, 2005.

X. Xiong, M.F. Mokbel, and W.G. Aref, “Sea-Cnn: Scalable Processing of relentless k-Nearest close by QueriesTemporal Databases,” Proc. IEEE Int’l Conf. facts and figures Eng., pp. 643-654,2005.

X. Yu, K.Q. Pu, and N. Koudas, “Monitoring k-Nearest close byQueries over Moving Objects,” Proc. 21st Int’l Conf. facts.

K. Mouratidis, D. Papadias, S. Bakiras, and Y. Tao, “A Threshold-Based Algorithm for Continuous Monitoring of k closest Neighbors,” IEEE Trans. Knowledge facts and figures Eng., vol. 17, no. 10,pp. 1451-1464, Nov. 2005.

M.A. Cheema, Y. Yuan, and X. Lin, “Circulartrip: An productiveAlgorithm for relentless Knn Queries,” Proc. 12th Int’l Conf. Database schemes for Advanced submissions, pp. 863-869, 2007.

N. Beckmann, H.-P.Kriegel, R. Schneider, and B. Seeger, “The R-Tree: An Efficient and robust Access Method for Points andRectangles,” Proc. ACM SIGMOD Int’l Conf. Management of facts pp. 322-331, 1990.

F. Aurenhammer, “Voronoi Diagrams - A review of a FundamentalGeometric facts and figures Structure,” ACM Computing reviews, vol. 23, no. 3, pp. 345-405, Sept. 1991.

B. Zheng, J. Xu, W.-C. Lee, and D.L. Lee, “Grid-Partition Index: A Hybrid procedure for Nearest-Neighbor Queries in Wireless position-founded Services,” The VLDB J., vol. 15, no. 1, pp. 21-39, Jan. 2006.

J. Zhang, M. Zhu, D. Papadias, Y. Tao, and D.L. Lee, “Location-founded Spatial Queries,” Proc. ACM SIGMOD Int’l Conf. Management of facts and figures, pp. 443-454, 2003.

Y. Tao and D. Papadias, “Time-Parameterized Queries in Spatio-Temporal Databases,” Proc. ACM SIGMOD Int’l Conf. administration of facts and figures, pp. 334-345, 2002.

S. Nutanong, R. Zhang, E. Tanin, and L. Kulik, “The V -Diagram: A Query-Dependent Method for going kNN Queries,” Proc. VLDB Conf., pp. 1095-1106, 2008.

L. Kulik and E. Tanin, “Incremental Rank revisions for goingQuery Points,” Proc. Int’l Conf. Geographic, data research, pp. 251-268, 2006.

S. Dar, M.J. Franklin, B.T. Jo´nsson, D. Srivastava, and M. Tan,“Semantic Data Caching and Replacement,” Proc. 22th Int’l Conf. Very Large facts and figures Bases, pp. 330-341, 1996.

W.-S. Ku, R. Zimmermann, and H. Wang, “Location-Based Spatial Query Processing in Wireless Broadcast Environments,” IEEE Trans. wireless Computing, vol. 7, no. 6, pp. 778-791, June 2008.

Z. Song and N. Rousso poulos, “K-Nearest close by Search forgoing Query Point,” Proc. Seventh Int’l Symp. Spatial and Temporal Databases, pp. 79-96, 2001.

A.A. Melkman, “On-Line Construction of the Convex Hull of aeasy Polyline,”




DOI: http://dx.doi.org/10.36039/AA082013004

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.