Processing Probabilistic Range Query over Imprecise Data Based on Quality of Result

Abstract

Sensors are employed in many applications to monitor entities such as environment temperature or illumination. Because of limited resources (e.g., battery power and wireless bandwidth), it is impractical for the database to track continuous changing readings from sensors at all times. Consequently, database may produce incorrect query results based on recorded data. However, if the error between the recorded value and the actual value is bounded, probabilistic approach can be applied to process queries over the imprecise data in database. The paper proposes a quality of result based probabilistic range query processing method. Two measures are defined to evaluate the quality of result. A probability model is proposed to estimate the quality of returned results. Based on the model, an algorithm is developed to choose the probability threshold according to user’s requirement on the quality of result.

This work was partially funded by the Key Program of the National Natural Science Foundation of China, Grant No. 60533110, by the National Natural Science Foundation of China, Grant No. 60473075, and by the key Natural Science Foundation of Heilongjiang Province, Grant No. zjg03-05.