IEEE Transactions on Computers
A generic framework for monitoring continuous spatial queries over moving objects
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A Threshold-Based Algorithm for Continuous Monitoring of k Nearest Neighbors
IEEE Transactions on Knowledge and Data Engineering
Evaluating continuous probabilistic queries over imprecise sensor data
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Probabilistic filters: A stream protocol for continuous probabilistic queries
Information Systems
| Hi-index | 0.00 |
Continuous spatial queries retrieve a set of time-varying objects continuously during a given period of time. However, monitoring moving objects to maintain the correctness of the query results often incurs frequent location updates from these moving objects. To address this problem, existing solutions propose lazy updates, but such techniques generally avoid only a small fraction of all unnecessary location updates because of their basic approach (e.g., safe regions, time or distance thresholds). In this paper, we introduce an Adaptive Safe Region (ASR) technique that retrieves an adjustable safe region which is continuously reconciled with the surrounding dynamic queries. In addition, we design a framework that supports multiple query types (e.g., range and c-k NN queries). In this framework, our query re-evaluation algorithms take advantage of ASRs and issue location probes only to the affected data objects. Simulation results confirm that the ASR concept improves scalability and efficiency over existing methods by reducing the number of updates.