Visualization of behavior clustering of computer applications
AssigneeMicrosoft Technology Licensing, LLC
InventorTetsuo Seto
Life of this patent
Estimating the term…
Abstract
Dimensionality reduction, such as principal component analysis, may be performed against a time series of performance observations for a computer application. A visual representation of the results may be displayed in one, two, or three dimensions, and often show clusters of operational behavior. The representation may be animated to show a sequence of observations and how the behavior of an application may change from one cluster of operation to another. The representation may be further applied to show both a historical view of the observations and new observations. The time series may contain performance and operational data, as well as metadata observed from a computer application.
Claims20
A method performed at a computer system comprising one or more processors, for displaying one or more dimensionally transformed datasets, the method comprising:
- generating, at the computer system, a dimensionality reduction transformation function representing a first time series, including at least:
- receiving, at the computer system, the first time series collected from tracing a computer application at a first time, the first time series comprising performance data for a plurality of functions of the computer application observed while tracing the computer application at the first time;
- processing, at the computer system, the first time series data into one or more time series vectors;
- and
- creating, at the computer system, a dimensionality reduction transformation function by identifying one or more principal components within the one or more time series vectors;
- receiving, at the computer system, a second time series collected from tracing the computer application at a second time;
- applying, at the computer system, the dimensionality reduction transformation function to the first time series and the second time series to generate a transformed dataset comprising at least the identified principal components of the first time series and the second time series;
- and
- causing the transformed dataset to be displayed at a display of the computer system.
A system comprising:
- at least one computer processor;
- a dimensionality reduction analyzer, executing on the at least one computer processor, that is configured to:
- generate a dimensionality reduction transformation function representing a first time series, including at least:
- receiving the first time series collected from tracing a computer application at a first time, the first time series comprising performance data for a plurality of functions of the computer application at the first time;
- processing the first time series data into one or more time series vectors;
- and
- creating a dimensionality reduction transformation function by identifying one or more principal components within the one or more time series vectors;
- and
- a display engine that:
- receives a second time series collected from tracing the computer application at a second time;
- applies the dimensionality reduction transformation function to the first time series and the second time series to generate a transformed dataset comprising at least the identified principal components of the first time series and the second time series;
- and
- causes the transformed dataset to be displayed at a display of the computer system.
Dependencies are inferred from the claim text.