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In recent years, the authors have witnessed the emergence of new types of systems that deal with large volumes of streaming data. Examples include financial data analysis on feeds of stock tickers, sensor-based environmental monitoring, network track monitoring and click stream analysis to push customized advertisements or intrusion detection. Traditional DataBase Management Systems (DBMS), which are very good at managing large volumes of stored data, are not suitable for this, as streaming needs low-latency processing on live data from push-based sources. Data Stream Management Systems (DSMS) are fast emerging to address this new type of data, but faces challenging issues, such as unpredictable data arrival rate.
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