Abstract:

Recently there has witnessed emergence of uncertain data streams,with features of time-varying,uncertain,unpredictable and continuous,in many new application.The data process encounters many technical challenges,such as limited memory,very short response time,continuous processing and so on.Window join is one of the difficult problems as it cost many resources.Focusing on the problems on high-speed processing and memory overflow,a series of algorithms are proposed to tackle simultaneous window joins over large scale uncertain data streams.On this basis,an original application to monitor clone cars is presented.Experiments with real data,uniform data and Gaussian data show that the algorithms gain good performance,and its processing speeds faster than the memory database（Timesten）2～8times,to meet the requirements of monitoring clone cars in real traffic.

Key words: uncertain data stream, window join, memory overflow, concurrent computation