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Pre-Filtering based Post-Load Shedding Method for Improving Spatial Queries Accuracy in GeoSensor Environment  

Kim, Ho (인하대학교 컴퓨터정보공학과)
Baek, Sung-Ha (인하대학교 컴퓨터정보공학과)
Lee, Dong-Wook (인하대학교 컴퓨터정보공학과)
Kim, Gyoung-Bae (서원대학교 컴퓨터교육과)
Bae, Hae-Young (인하대학교 컴퓨터정보공학과)
Publication Information
Journal of Korea Spatial Information System Society / v.12, no.1, 2010 , pp. 18-27 More about this Journal
Abstract
In u-GIS environment, GeoSensor environment requires that dynamic data captured from various sensors and static information in terms of features in 2D or 3D are fused together. GeoSensors, the core of this environment, are distributed over a wide area sporadically, and are collected in any size constantly. As a result, storage space could be exceeded because of restricted memory in DSMS. To solve this kind of problems, a lot of related studies are being researched actively. There are typically 3 different methods - Random Load Shedding, Semantic Load Shedding, and Sampling. Random Load Shedding chooses and deletes data in random. Semantic Load Shedding prioritizes data, then deletes it first which has lower priority. Sampling uses statistical operation, computes sampling rate, and sheds load. However, they are not high accuracy because traditional ones do not consider spatial characteristics. In this paper 'Pre-Filtering based Post Load Shedding' are suggested to improve the accuracy of spatial query and to restrict load shedding in DSMS. This method, at first, limits unnecessarily increased loads in stream queue with 'Pre-Filtering'. And then, it processes 'Post-Load Shedding', considering data and spatial status to guarantee the accuracy of result. The suggested method effectively reduces the number of the performance of load shedding, and improves the accuracy of spatial query.
Keywords
GeoSensor Network; Data Stream; Load Shedding; Filtering;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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