Scientific and Statistical Database Management

Volume 6809 of the series Lecture Notes in Computer Science pp 150-167

Efficient Processing of Multiple DTW Queries in Time Series Databases

  • Hardy KremerAffiliated withRWTH Aachen University
  • , Stephan GünnemannAffiliated withRWTH Aachen University
  • , Anca-Maria IvanescuAffiliated withRWTH Aachen University
  • , Ira AssentAffiliated withAarhus University
  • , Thomas SeidlAffiliated withRWTH Aachen University

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Dynamic Time Warping (DTW) is a widely used distance measure for time series that has been successfully used in science and many other application domains. As DTW is computationally expensive, there is a strong need for efficient query processing algorithms. Such algorithms exist for single queries. In many of today’s applications, however, large numbers of queries arise at any given time. Existing DTW techniques do not process multiple DTW queries simultaneously, a serious limitation which slows down overall processing.

In this paper, we propose an efficient processing approach for multiple DTW queries. We base our approach on the observation that algorithms in areas such as data mining and interactive visualization incur many queries that share certain characteristics. Our solution exploits these shared characteristics by pruning database time series with respect to sets of queries, and we prove a lower-bounding property that guarantees no false dismissals. Our technique can be flexibly combined with existing DTW lower bounds or other single DTW query speed-up techniques for further runtime reduction. Our thorough experimental evaluation demonstrates substantial performance gains for multiple DTW queries.