Generating simulation data using a linear curve simplification and reverse simplification method
AssigneeQuest Software, Inc.
InventorsShengzhi Liu, Peisen Lin, Yinghua Qin
Life of this patent
Estimating the term…
Abstract
Simulation data can be generated using a linear curve simplification and reverse simplification technique. The linear curve simplification and reverse simplification technique can facilitate the generation of simulation data from existing data where the simulation data will exhibit the same curve pattern as the existing data but with a degree of variation. In this way, varying sets of simulation data for a particular environment can be easily generated.
Claims20
A method, performed by a computing system that includes a simplification engine and a reverse simplification engine, for generating simulation data for testing a subject computing system based on existing data for the subject computing system by applying a simplification algorithm and a reverse simplification algorithm to the existing data to generate the simulation data with a controllable degree of individual distinction from the existing data such that the simulation data represents resource utilization variations that may actually occur when the subject computing system is executing, the method comprising:
- obtaining, by the simplification engine, the existing data that comprises a series of points where each point represents resource utilization of the subject computing system at a particular time;
- applying, by the simplification engine, the simplification algorithm to the existing data to convert the existing data into a reduced set of characteristic points, wherein the simplification engine employs a particular value of a parameter to calculate which of the points of the existing data are characteristic points;
- receiving, by the reverse simplification engine and from the simplification engine, the reduced set of characteristic points and the particular value of the parameter;
- calculating, by the reverse simplification engine, simulation data with a degree of individual distinction from the existing data by:
- for each adjacent pair of characteristic points, defining a reverse simplification data sample zone using the particular value of the parameter;
- for each defined reverse simplification data sample zone, generating a number of additional points that fall within the reverse simplification data sample zone;
- and
- combining the number of additional points generated for each defined reverse simplification data sample zone along with the characteristic points to thereby produce the simulation data;
- and
- testing the subject computing system using the simulation data.
One or more computer storage media storing computer executable instructions which when executed by one or more processors implement a method for generating simulation data for testing a subject computing system based on existing data for the subject computing system by applying a simplification algorithm and a reverse simplification algorithm to the existing data to generate the simulation data with a controllable degree of individual distinction from the existing data such that the simulation data represents resource utilization variations that may actually occur when the subject computing system is executing, the method comprising:
- obtaining, by a simplification engine, the existing data that comprises a series of points where each point represents resource utilization of the subject computing system at a particular time;
- applying, by the simplification engine, the simplification algorithm to the existing data to convert the existing data into a reduced set of characteristic points, wherein the simplification engine employs a particular value of a parameter to calculate which of the points of the existing data are characteristic points;
- receiving, by a reverse simplification engine and from the simplification engine, the reduced set of characteristic points and the particular value of the parameter;
- calculating, by the reverse simplification engine, simulation data with a degree of individual distinction from the existing data by:
- for each adjacent pair of characteristic points, defining a reverse simplification data sample zone using the particular value of the parameter;
- for each defined reverse simplification data sample zone, generating a number of additional points that fall within the reverse simplification data sample zone;
- and
- combining the number of additional points generated for each defined reverse simplification data sample zone along with the characteristic points to thereby produce the simulation data;
- and
- testing the subject computing system using the simulation data.
A method, performed by a computing system that includes a simplification engine and a reverse simplification engine, for generating multiple sets of simulation data for testing a subject computing system based on existing data for the subject computing system by applying a simplification algorithm and a reverse simplification algorithm to the existing data to generate each of the multiple sets of simulation data with a controllable degree of individual distinction from the existing data such that each of the multiple sets of simulation data represents resource utilization variations that may actually occur when the subject computing system is executing, the method comprising:
- obtaining, by the simplification engine, the existing data that comprises a series of points where each point represents resource utilization of the subject computing system at a particular time;
- applying, by the simplification engine, the simplification algorithm to the existing data to convert the existing data into multiple reduced sets of characteristic points, wherein the simplification engine employs a different value of a parameter to calculate which of the points of the existing data are characteristic points in each of the multiple reduced sets of the characteristic points;
- receiving, by the reverse simplification engine and from the simplification engine, the multiple reduced sets of characteristic points and the corresponding values of the parameter;
- calculating, by the reverse simplification engine, multiple sets of simulation data where each set of simulation data exhibits a different degree of individual distinction from the existing data, each set of simulation data being calculated using a corresponding reduced set of characteristic points and a corresponding value of the parameter by:
- for each adjacent pair of characteristic points in the corresponding reduced set of characteristic points, defining a reverse simplification data sample zone using the corresponding value of the parameter;
- for each defined reverse simplification data sample zone, generating a number of additional points that fall within the reverse simplification data sample zone;
- and
- combining the number of additional points generated for each defined reverse simplification data sample zone along with the characteristic points in the corresponding reduced set of characteristic points to thereby produce the set of simulation data;
- and
- testing the subject computing system using at least one of the sets of simulation data.
Dependencies are inferred from the claim text.