Sketching asynchronous streams over a sliding window

We study the problem of maintaining sketches of recent elements of a data stream. Motivated by applications involving network data, we consider streams that are asynchronous, in which the observed order of data is not the same as the time order in which the data was generated. The notion of recent elements of a stream is modeled by the sliding timestamp window, which is the set of elements with timestamps that are close to the current time. We design algorithms for maintaining sketches of all elements within the sliding timestamp window that can give provably accurate estimates of two basic aggregates, the sum and the median, of a stream of numbers. The space taken by the sketches, the time needed for querying the sketch, and the time for inserting new elements into the sketch are all polylog with respect to the maximum window size and the values of the data items in the window. Our sketches can be easily combined in a lossless and compact way, making them useful for distributed compu...

• Type: Conference
• Year: 2006
• Where: PODC
• Authors: Srikanta Tirthapura, Bojian Xu, Costas Busch
• Keywords: Data Stream, Distributed And Parallel Computing, Observed Order, PODC 2006, Timestamp Window