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Privacy Conscious Screening Framework for Frequently Moving Objects


Affiliations
1 Department of Computer Science and Engineering, Sardar Raja College of Engineering, Alangulam, Tirunelveli, India
     

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The fundamental problem in any monitoring system is when and how a mobile client should send location updates to the server, because it determines three principal performance measures such as monitoring accuracy, efficiency, and privacy. In this paper the clients considered as, are privacy conscious. The PCS is the comprehensive framework that addresses the issue of location updating holistically with monitoring accuracy, efficiency, and privacy altogether. This framework extends from the previous work by introducing a common privacy model, and therefore, suits realistic scenarios. We incorporate other types of queries into the framework, such as spatial joins and aggregate queries. We optimize the performance of the framework by sequentially optimizing the queries but maintain the safe region accumulated by the queries optimized so far.


Keywords

Spatial Databases, Location-Dependent and Sensitive, Mobile Applications, Global Safe Region.
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Abstract Views: 194

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  • Privacy Conscious Screening Framework for Frequently Moving Objects

Abstract Views: 194  |  PDF Views: 3

Authors

S. Ganesh
Department of Computer Science and Engineering, Sardar Raja College of Engineering, Alangulam, Tirunelveli, India
V. S. Dhanyasree
Department of Computer Science and Engineering, Sardar Raja College of Engineering, Alangulam, Tirunelveli, India

Abstract


The fundamental problem in any monitoring system is when and how a mobile client should send location updates to the server, because it determines three principal performance measures such as monitoring accuracy, efficiency, and privacy. In this paper the clients considered as, are privacy conscious. The PCS is the comprehensive framework that addresses the issue of location updating holistically with monitoring accuracy, efficiency, and privacy altogether. This framework extends from the previous work by introducing a common privacy model, and therefore, suits realistic scenarios. We incorporate other types of queries into the framework, such as spatial joins and aggregate queries. We optimize the performance of the framework by sequentially optimizing the queries but maintain the safe region accumulated by the queries optimized so far.


Keywords


Spatial Databases, Location-Dependent and Sensitive, Mobile Applications, Global Safe Region.