An Effective Uncertain Data Streams Top-K Query Algorithm

摘要

Large scale uncertain data streams are produced in many modern applications, such as RFID technology andsensor networks. Top-K query processing is one of the important techniques in the management of uncertain data streams.Existing Top-K queries processing does not consider the score and uncertainty of tuples. This paper first analyzes the uncertaindata model and possible world semantic model, and then defines new Top-K queries semantics for uncertain datastreams, and finally designs and realizes an effective Top-K queries algorithm on uncertain data streams. This algorithmsorts the score of each tuple and selects the k tuples with the highest probabilities to form the set, Top-K queries results.Compared to CSQ and SCSQ algorithm, the experiments show that this algorithm is more practical and effective than theothers.