Minimization of Suffix Array´s Storage Capacity for Periodicity Detection in Time Series

In everyday life bulk amount of time-stamped data is accumulated in diverse databases. Such data may be mapped into a time-based representation forming very long time series which could be effectively analyzed for valuable knowledge discovery. However, most of the times analyzing these time series has been proven a very complicated task especially when they are very large. This paper tackles the problem by proposing an optimization method for storing very large time series in suffix arrays for further analysis, and repeated pattern detection is proposed as well. Based on this method, the required part of the time series to be stored for repeated pattern detection can be reduced by at least 25%. The method was applied to DNA chains with length up to 100,000,000 characters long and the corresponding results are presented.