Yuan-Ko Huang’s research while affiliated with Kao Yuan University and other places

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Publications (1)


Table 1 . System parameters.
Grid deployment.
Uncertainty model.
Grid index.
Update mechanism.

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Processing KNN Queries in Grid-Based Sensor Networks
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October 2014

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5 Citations

Yuan-Ko Huang

Recently, developing efficient processing techniques in spatio-temporal databases has been a much discussed topic. Many applications, such as mobile information systems, traffic control system, and geographical information systems, can benefit from efficient processing of spatio-temporal queries. In this paper, we focus on processing an important type of spatio-temporal queries, the K-nearest neighbor (KNN) queries. Different from the previous research, the locations of objects are located by the sensors which are deployed in a grid-based manner. As the positioning technique used is not the GPS technique, but the sensor network technique, this results in a greater uncertainty regarding object location. With the uncertain location information of objects, we try to develop an efficient algorithm to process the KNN queries. Moreover, we design a probability model to quantify the possibility of each object being the query result. Finally, extensive experiments are conducted to demonstrate the efficiency of the proposed algorithms.

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Citations (1)


... Hence, the Continuous k-NN querying in real-time and dynamic environments has attracted the attention of researchers [21]. In [22], the authors attempt to develop an efficient algorithm to process the k-NN queries on uncertain locations of objects. A probability model is designed to quantify the possibility of each object being one of the k nearest neighbors. ...

Reference:

Trajectory Clustering and k-NN for Robust Privacy Preserving k-NN Query Processing in GeoSpark
Processing KNN Queries in Grid-Based Sensor Networks