Patent ID: 8001093

Claim:
A computer-implemented method for purging timeseries data samples stored in a repository, said method comprising: calculating, by a computer, a utility value for each data sample of a measurement timeseries and an event timeseries, respectively, of monitored IT infrastructure elements, wherein a calculation of said utility values is based on a dependency model being represented as a hierarchical graph having (i) nodes, and (ii) edges among nodes of a same level of said hierarchical graph, and each said measurement and event timeseries being associated with a node, wherein said event timeseries has a dependency relationship to said measurement timeseries, and wherein said measurement and event timeseries are segmented into time windows of a fixed size and window boundaries are synchronized for said measurement and event timeseries; changing, by said computer, said utility values of all data samples assigned to selected windows in said measurement and event timeseries within a temporal distance of an event that occurs in said event timeseries; determining, by said computer, an information content and an average utility value of each said data sample in each of said selected windows, wherein said determining of said information content of each said data sample is performed on the basis of using one of a probability distribution function, a mean square error, and a Kullback Liebler distance applied to said data samples; and purging, by said computer, said data samples from each of said selected windows that are to be stored in said repository of fixed size, such that said data samples having high utility value are retained and loss of said information content of retained data samples is minimized, wherein said number of data samples in said selected windows to be stored in said repository is proportional to a product of said average utility and said information content of said data samples in said selected windows, divided by a sum of products of an average utility and an information content for all windows of said measurement and event timeseries.