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Author Sun, Jimeng ♦ Papadias, Dimitris ♦ Tao, Yufei ♦ Liu, Bin
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Efficient Management ♦ Large Amount ♦ Novel Approach ♦ On-line Computation ♦ Dynamic Nature ♦ Challenging Goal ♦ Present-time Query ♦ Spatio-temporal Database ♦ Stochastic Approach ♦ Spatio-temporal Information ♦ Road Network ♦ Multi-dimensional Histogram ♦ In ICDE ♦ Historical Data ♦ General Architecture ♦ Realistic Simulation ♦ Approximate Query Processing ♦ Data Stream
Description Moving objects (e.g., vehicles in road networks) continuously generate large amounts of spatio-temporal information in the form of data streams. Efficient management of such streams is a challenging goal due to the highly dynamic nature of the data and the need for fast, on-line computations. In this paper we present a novel approach for approximate query processing about the present, past, or the future in spatio-temporal databases. In particular, we first propose an incrementally updateable, multi-dimensional histogram for present-time queries. Second, we develop a general architecture for maintaining and querying historical data. Third, we implement a stochastic approach for predicting the results of queries that refer to the future. Finally, we experimentally prove the effectiveness and efficiency of our techniques using a realistic simulation. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2004-01-01