Publication | Closed Access
A generic framework for monitoring continuous spatial queries over moving objects
255
Citations
25
References
2005
Year
Unknown Venue
EngineeringLocalizationSpatiotemporal DatabaseLocation-based ServiceData ScienceLocation AwarenessSpatial Data ManagementInternet Of ThingsData ManagementSafe RegionSpatial DatabasesContinuous Spatial QueriesComputer ScienceMobile ComputingMobile Positioning DataSpatio-temporal Stream ProcessingEdge ComputingGeneric FrameworkSafe Region ComputationSpatio-temporal ModelLocation InformationLocation ManagementData Modeling
The authors introduce a generic framework that monitors continuous spatial queries over moving objects, uniquely addressing the location‑update problem and offering a unified interface for mixed query types. The framework employs a safe‑region based client update strategy, with algorithms for query evaluation, safe‑region computation, and optimizations exploiting maximum speed and steady movement assumptions. Experiments demonstrate that the framework markedly reduces wireless communication and query reevaluation costs, surpasses periodic monitoring in accuracy and CPU time, achieves near‑optimal communication overhead, and scales robustly across diverse mobility patterns.
This paper proposes a generic framework for monitoring continuous spatial queries over moving objects. The framework distinguishes itself from existing work by being the first to address the location update issue and to provide a common interface for monitoring mixed types of queries. Based on the notion of safe region, the client location update strategy is developed based on the queries being monitored. Thus, it significantly reduces the wireless communication and query reevaluation costs required to maintain the up-to-date query results. We propose algorithms for query evaluation/reevaluation and for safe region computation in this framework. Enhancements are also proposed to take advantage of two practical mobility assumptions: maximum speed and steady movement. The experimental results show that our framework substantially outperforms the traditional periodic monitoring scheme in terms of monitoring accuracy and CPU time while achieving a close-to-optimal wireless communication cost. The framework also can scale up to a large monitoring system and is robust under various object mobility patterns.
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