Resource provisioning using predictive modeling in a networked computing environment
View Patent ↗An approach is provided for allowing a network computing (e.g., cloud computing) infrastructure to modify its resource allocation plan (e.g., an instance count) by using a Kth derivative vector plot, which may be generated using historical logs. Among other things, this approach enables an infrastructure to project an allocation forecast for a specified duration and adapt to changes in network traffic.
1. A computer-implemented method for provisioning computing resources using predictive modeling in a networked computing environment, comprising:
accessing a set of graphical curves of network data traffic versus time, the set of graphical curves being stored in at least one computer storage device;
segmenting the set of graphical curves into a set of predetermined time intervals to yield a set of time interval curves;
overlaying and fitting the set of time interval curves to yield a set of best fit overlaying curves;
generating a derivative vector plot based on a set of data points of the set of best fit overlaying curves; and
forecasting network traffic in the networked computing environment based on the derivative vector plot.
2. The computer-implemented method of claim 1 , further comprising provisioning a set of computing resources in the networked computing environment based on the forecasted network traffic.
3. The computer-implemented method of claim 1 , the derivative vector plot comprising a K th derivative vector plot being generated by transforming the set of data points using a mathematical algorithm.
4. The computer-implemented method of claim 3 , further comprising outputting a network traffic projection based on the forecasting.
5. The computer-implemented method of claim 4 , the network traffic projection being generated by integrating K initial conditions a K quantity of times using a predetermined numerical technique.
6. The computer-implemented method of claim 3 , the mathematical algorithm comprising a fourth order Runge-Kutta method.
7. The computer-implemented method of claim 1 , the networked computing environment comprising a cloud computing environment.
8. A system for provisioning computing resources using predictive modeling in a networked computing environment, comprising:
a memory medium comprising instructions;
a bus coupled to the memory medium; and
a processor coupled to the bus that when executing the instructions causes the system to:
access a set of graphical curves of network data traffic versus time, the set of graphical curves being stored in at least one computer storage device;
segment the set of graphical curves into a set of predetermined time intervals to yield a set of time interval curves;
overlay and fit the set of time interval curves to yield a set of best fit overlaying curves;
generate a derivative vector plot based on a set of data points of the set of best fit overlaying curves; and
forecast network traffic in the networked computing environment based on the derivative vector plot.
9. The system of claim 8 , the memory medium further comprising instructions for causing the system to provision a set of computing resources in the networked computing environment based on the forecasted network traffic.
10. The system of claim 8 , the derivative vector plot comprising a K th derivative vector plot, the memory medium further comprising instructions for causing the system to transforming the set of data points using a mathematical algorithm to yield the K th derivative vector plot.
11. The system of claim 10 , the memory medium further comprising instructions for causing the system to output a network traffic projection based on the forecasting.
12. The system of claim 11 , the network traffic projection being generated by integrating K initial conditions of a K quantity of times using a predetermined numerical technique.
13. The system of claim 10 , the mathematical algorithm comprising a fourth order Runge-Kutta method.
14. The system of claim 8 , the networked computing environment comprising a cloud computing environment.
15. A computer program product for provisioning computing resources using predictive modeling in a networked computing environment, the computer program product comprising a computer readable storage device, and program instructions stored on the computer readable storage device, to:
access a set of graphical curves of network data traffic versus time, the set of graphical curves being stored in at least one computer storage device;
segment the set of graphical curves into a set of predetermined time intervals to yield a set of time interval curves;
overlay and fit the set of time interval curves to yield a set of best fit overlaying curves;
generate a derivative vector plot based on a set of data points of the set of best fit overlaying curves; and
forecast network traffic in the networked computing environment based on the derivative vector plot.
16. The computer program product of claim 15 , the computer readable storage media further comprising instructions to provision a set of computing resources in the networked computing environment based on the forecasted network traffic.
17. The computer program product of claim 15 , the derivative vector plot comprising a K th derivative vector plot, the computer readable storage media further comprising instructions to transforming the set of data points using a mathematical algorithm to yield the K th derivative vector plot.
18. The computer program product of claim 17 , the computer readable storage media further comprising instructions to output a network traffic projection based on the forecasting.
19. The computer program product of claim 18 , the network traffic projection being generated by integrating K initial conditions a K quantity of times using a predetermined numerical technique.
20. The computer program product of claim 17 , the mathematical algorithm comprising a fourth order Runge-Kutta method.
21. The computer program product of claim 15 , the networked computing environment comprising a cloud computing environment.
22. A method for deploying a system for provisioning computing resources using predictive modeling in a networked computing environment, comprising:
providing a computer infrastructure being operable to:
access a set of graphical curves of network data traffic versus time, the set of graphical curves being stored in at least one computer storage device;
segment the set of graphical curves into a set of predetermined time intervals to yield a set of time interval curves;
overlay and fit the set of time interval curves to yield a set of best fit overlaying curves;
generate a derivative vector plot based on a set of data points of the set of best fit overlaying curves; and
forecast network traffic in the networked computing environment based on the derivative vector plot.