A safe-exit approach for efficient network-based moving range queries
Data & Knowledge Engineering
Continuous reverse k nearest neighbors queries in Euclidean space and in spatial networks
The VLDB Journal — The International Journal on Very Large Data Bases
Efficiently processing snapshot and continuous reverse k nearest neighbors queries
The VLDB Journal — The International Journal on Very Large Data Bases
Authentication of moving range queries
Proceedings of the 21st ACM international conference on Information and knowledge management
A safe zone based approach for monitoring moving skyline queries
Proceedings of the 16th International Conference on Extending Database Technology
Efficient batch processing of proximity queries by optimized probing
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Efficient Monitoring of Moving Mobile Device Range Queries using Dynamic Safe Regions
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
Service-oriented middleware for large-scale mobile participatory sensing
Pervasive and Mobile Computing
Mobile Information Systems
A safe exit algorithm for continuous nearest neighbor monitoring in road networks
Mobile Information Systems
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Given a positive value r, a distance-based range query returns the objects that lie within the distance r of the query location. In this paper, we focus on the distance-based range queries that continuously change their locations in a euclidean space. We present an efficient and effective monitoring technique based on the concept of a safe zone. The safe zone of a query is the area with a property that while the query remains inside it, the results of the query remain unchanged. Hence, the query does not need to be reevaluated unless it leaves the safe zone. Our contributions are as follows: 1) We propose a technique based on powerful pruning rules and a unique access order which efficiently computes the safe zone and minimizes the I/O cost. 2) We theoretically determine and experimentally verify the expected distance a query moves before leaving the safe zone and, for majority of queries, the expected number of guard objects. 3) Our experiments demonstrate that the proposed approach is close to optimal and is an order of magnitude faster than a naïve algorithm. 4) We also extend our technique to monitor the queries in a road network. Our algorithm is up to two order of magnitude faster than a naïve algorithm.