IEEE Transactions on Knowledge and Data Engineering · 2005 · 107 citations · 21 references
Cluster ComputingEngineeringStreaming AlgorithmData Streaming ArchitectureLocalizationSpatiotemporal DatabaseMeasurement NetworkNearest Neighbor SetMonitoring TechnologyContinuous MonitoringData ScienceData MiningPattern RecognitionData ManagementCentral ServerK Nearest NeighborsMachine VisionSensor Signal ProcessingKnowledge DiscoveryComputer ScienceMobile ComputingData Stream ManagementSignal ProcessingSpatio-temporal Stream ProcessingEdge ComputingBusinessNetwork MonitoringBig Data
Assume a set of moving objects and a central server that monitors their positions over time, while processing continuous nearest neighbor queries from geographically distributed clients. In order to always report up-to-date results, the server could constantly obtain the most recent position of all objects. However, this naive solution requires the transmission of a large number of rapid data streams corresponding to location updates. Intuitively, current information is necessary only for objects that may influence some query result (i.e., they may be included in the nearest neighbor set of some client). Motivated by this observation, we present a threshold-based algorithm for the continuous monitoring of nearest neighbors that minimizes the communication overhead between the server and the data objects. The proposed method can be used with multiple, static, or moving queries, for any distance definition, and does not require additional knowledge (e.g., velocity vectors) besides object locations.
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Nick Roussopoulos, Stephen Kelley, F. Vincent · 1995 · 1.4K citations · Full text
Engineering, Geographic Information Retrieval, Range Queries +18
A Framework for Generating Network-Based Moving Objects
Thomas Brinkhoff · GeoInformatica · 2002 · 862 citations
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Christine E. Jones, Krishna M. Sivalingam, Prathima Agrawal et al. · Wireless Networks · 2001 · 833 citations
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